JP2008160704A - Density correction curve generation method and density correction curve generation module - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To generate a density correction curve for making a pure white dress in a bridal photograph image photographed under compound photographic conditions. <P>SOLUTION: A density histogram is determined from the bridal photograph image, a density value in which a ratio of a cumulative pixel number from the highlight side of the density histogram to the number of all pixels becomes a first predetermined value is calculated as a highlight side saturation density value, the highlight side saturation density value is adjusted by an adjustment value which is calculated on the basis of predetermined bridal image characteristics of the bridal photograph image, and a density correction curve is generated with the adjusted highlight side saturation density value as a highlight side saturation point. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a technique for generating a density correction curve for a bridal photographed image obtained by photographing a bridal scene.

  At present, in the photographic printing industry, it has been obtained by digitizing a photographed image data obtained by digitizing a photographed image formed on a photographic film using a film scanner or a digital photographing device such as a digital camera. The captured image data (hereinafter simply abbreviated as the captured image) is subjected to image processing such as density correction and color correction, and then converted into print data, and the print exposure unit is driven based on the print data to capture the captured image. The mainstream is digital photographic processing technology for printing photographic materials on photographic materials (photographic paper) to produce photographic prints.

  In the field of such digital photo processing technology, in order to produce an appropriate photo print, for each color component (for example, R: red, G: green, B: blue) of the pixels constituting the input photographed image. Processing for correcting the density value is performed. As such a density correction method, density correction by a density correction curve (gamma correction) is generally used. In other words, since the density gradation that the photographic paper develops does not match the density gradation of the input photographed image, the density gradation that the photographic paper develops is set to be suitable for human visual characteristics. The input image data is corrected using the correction curve, and the density gradation that is colored on the photographic print (printing paper) finally obtained based on the corrected output image data corresponds to the human visual characteristics. I try to be something. As the density correction curve, a basic density correction curve created based on theoretical and empirical knowledge is well known and used. However, the subject situation and the shooting environment situation of the shot image are various, and the simple basic density correction curve cannot obtain appropriate output image data depending on the shooting scene of the input shot image data. Has occurred. For example, when correcting photographic image data captured from photographic film taken with over / under exposure (overexposure / underexposure), the brightness of each pixel constituting the photographic image data is low (shadow) or high. The output density is very weak with respect to the input density because the slope of the shadow part and highlight part in the basic density correction curve is moderate, while the brightness (highlight part) is too biased. Will be corrected.

  Therefore, in order to perform an appropriate density correction for a human photographed image including a face area, an area that is likely to include a feature amount of RGB data of a pixel having a hue corresponding to the skin color of the person and a person. There has been known a technique devised so that the density of a person is appropriately corrected by correcting the density correction curve based on the feature value of the RGB data of each pixel (see Patent Document 1).

  In addition, judgment using pattern matching, neural network, etc. in order to create appropriate photo prints from captured images where the main subject such as a person is crushed black or white A determination process for determining whether a main subject such as a person's face or person extracted by the method has backlight or high contrast, and a shadow of scene reference image data when the determination process determines backlight or high contrast. There is known an image processing method including a specifying step for specifying a side saturation point and a highlight side saturation point, and a gradation correction step for changing the brightness of the main subject (see, for example, Patent Document 2). At that time, the average values of the luminance (density values) at which the cumulative values on the shadow side and highlight side of the cumulative luminance histogram are 0.1 to 0.4% of the total are the shadow side saturation point and the highlight side saturation, respectively. After being specified as a point, gradation correction (density correction) is performed.

  In such a density correction technique, when it is clear that the captured image to be processed is a backlight scene or a high contrast scene, an effect as expected can be obtained. However, there are cases in which captured images are called composite imaging conditions in which various imaging conditions (backlight scenes, high contrast scenes, tungsten scenes, etc.) overlap, and in such cases, good results cannot be obtained. In particular, as a photographed image in which such a superposed photographing scene is likely to occur, a bridal photographed image in which a bride and groom at a wedding ceremony (especially a bride wearing a pure white wedding dress or a white strip) is a subject can be cited. In such a bridal photographed image, first, a photo print in which the pure white costume looks pure white is expected regardless of the photographing conditions, whereas the above-described conventional density correction technique has not provided sufficient results. .

  Of course, as a technology for simply finishing a whitish color region to white, for example, characters of a color photographed image such as characters on a white board which is not pure white are made clear and easy to see by correcting unevenness in illuminance, so that the color components of the three primary colors are used. For an image composed of pixel signals, a predetermined white background level is calculated for each color component image using the pixel signal of each color component, and the level of the pixel signal equal to or higher than the calculated white background level is converted to a predetermined saturation level. A technique is known in which a γ characteristic is set for each color component, and a captured image is subjected to gamma correction using the γ characteristic (see, for example, Patent Document 3). In this technology (digital camera), a class having the maximum frequency is set within the range corresponding to the white background portion of the histogram of the pixel data of the green component constituting the image of the highlight image, with the saturation level on the highlight side in this γ characteristic. ing. In other words, if a histogram of the level distribution of the pixel data of the green component is created for an image of a white board on which characters, figures, etc. are drawn, generally a mountain and a black part (character part) corresponding to the white background part (board part) The level corresponding to the peak of the mountain corresponding to the white background portion is set as the highlight side saturation level of the γ characteristic. Even if this technology is effective for extreme density correction to make it easier to see characters on the whiteboard, it is not suitable for the purpose of making the bride's costume stand out without destroying the overall color in the bridal image. It is.

JP 2002-369020 A (paragraph number 0004-0008, FIG. 5) JP 2005-209012 (paragraph number 0006-0015, FIG. 4) JP-A-10-210287 (paragraph numbers 0016-0018, 0091)

  In view of the above situation, an object of the present invention is to obtain a pure white color in a bridal photographed image obtained by photographing a bridal scene that tends to be a complex photographing adverse condition such as a backlight photographing condition, a strobe photographing condition, and a tungsten illumination photographing condition. It is to provide a technique for generating a density correction curve that makes an outfit stand out.

  In order to solve the above-described problem, a density correction curve generation method for a bridal photographed image obtained by photographing a bridal scene according to the present invention includes a step of obtaining a density histogram from the bridal photographed image, Calculating a density value at which a ratio of the cumulative number of pixels from the light side to the total number of pixels is a first predetermined value as a highlight side saturated density value; and the highlight side saturated density value is a predetermined value of the bridal photographed image. The adjustment includes an adjustment value calculated based on the bridal image characteristics, and a step of generating a density correction curve using the adjusted highlight-side saturation density value as a highlight-side saturation point.

  Note that the term “correction curve” used in this specification has the same meaning as the conversion table used in pixel value conversion, and appropriate values for the original image pixel values, such as conversion formulas often used in the field of image processing, are used. This is a general term for a function for converting to a pixel value of an image. Further, not only a direct conversion function but also a data group for creating such a conversion function belongs to the range of the phrase. A conversion equation indicated by a straight line is also included in this correction curve.

  According to this method, the density value at which the ratio of the cumulative number of pixels from the highlight side of the density histogram of the bridal photographed image to be corrected to the total number of pixels is the first predetermined value is obtained as the highlight side saturated density value. Then, after obtaining a predetermined bridal image characteristic that is an inherent image characteristic of only this bridal photographed image, and adjusting the highlight side saturation density value using an adjustment value calculated based on the bridal image characteristic, A density correction curve is generated using the adjusted highlight side saturation density value as the highlight side saturation point. In density correction using this density correction curve, input values that exceed the saturation value on the highlight side are set to substantially the same maximum density value, so white colors that are slightly tinted in bridal images are also included. The white area is corrected to white. In other words, the bride's pure white outfit will be reproduced on the photo print as an outstanding white. In addition, since the highlight side saturation point uses the highlight side saturation density value adjusted based on the bridal image characteristic specific to the bridal photographed image to be corrected, the density histogram is similar, for example, If the bridal photographed image has a similar degree of black crushing, the inconvenience of the same density correction is solved, and the bridal photographed image correction suitable for the pattern is possible.

  The bride and the other subjects in the bridal image include the bridegroom and other participants, but considering that these people generally wear black dresses, the black side or shadow side is also considered. It is preferable to perform density correction unique to the bridal photographed image. Therefore, in one preferred embodiment of the present invention, the density value at which the ratio of the cumulative number of pixels from the shadow side of the density histogram to the total number of pixels is the second predetermined value is calculated as the shadow side saturated density value. And a step of adjusting the shadow-side saturation density value by an adjustment value calculated based on the bridal image characteristic, and the density correction using the adjusted shadow-side saturation density value as a shadow-side saturation point. The curve is corrected. As a result, the groom's black ground dress can be made to stand out, but since its importance is lower than the bride's costume, the second predetermined value is preferably set smaller than the first predetermined value.

  The first predetermined value can be obtained by statistical analysis of experimental results based on many standard bridal captured image samples. It is appropriate that the first predetermined value is 1 to 20%. More preferably, it is around 15%, but this is determined in advance according to the location of the wedding ceremony, the photographing equipment used, the photographing lighting conditions, and the like. This value of 1 to 20% is a high value that is unthinkable for a normal photographed image, but from a bridal photographed image photographed under unfavorable photographing conditions such as tungsten illumination and backlight, a pure white bride This is an effective value for producing photo prints with bright costumes. The second predetermined value that defines the shadow-side saturation density value is preferably smaller than the first predetermined value that defines the highlight-side saturation density value. This is because, in a bridal photographed image centered on indoor photographing, if the shadow side saturation point is increased, unnecessarily blackening may occur. For this reason, the second predetermined value is set to about 0.01 to 1%.

  As the bridal image characteristic that is a parameter for adjusting the saturation density value directly obtained from the analysis of the density histogram, first, the ratio of the bridal costume area in the entire area of the photographed image can be mentioned. In general, as the area ratio of bridal costumes increases, it is better to shift the saturation value on the highlight side to the lower side (shadow side) in order to make the white of the bridal costume stand out. If the ratio is exceeded, it will be necessary to reproduce the three-dimensional image by folding and overlapping the bridal gown, so highlight side saturation density value, that is, highlight side saturation point is moved to the highlight side. It is better to enrich the reproduction of white. To detect the bridal costume area from the bridal image, the face area is detected by a face detection algorithm that detects the face in the captured image and outputs face information such as the size, area, and orientation. It is advisable to combine the edge detection algorithm and the white detection algorithm at the bottom.

  Since the size of the bridal costume area can be estimated to some extent directly from the detected face area, the process of detecting the bridal costume area from the detected face area is omitted, and the face area occupying the entire area of the captured image is omitted. It is also possible to obtain the adjustment value directly from the ratio of the face area by using the ratio as the bridal image characteristic.

  As another bridal image characteristic, the ratio of the number of pixels having a density value equal to or higher than a preset highlight threshold to the total number of pixels of the photographed image can be given. When the percentage of pixels having a density value on the highlight side (for example, 200 or more in 8-bit gradation) is large in the density histogram, the value of the saturation density value on the highlight side is shifted to the higher side (highlight side). Adjust to enrich the reproduction of white.

  In the above method, it is optimal to calculate the highlight side saturation density value (in some cases, the shadow side saturation density value) for each color component (R, G, B). For the sake of simplicity, it may be calculated using a density value obtained by integrating color components generally called luminance, for example, (R + G + B) / 3.

  In the present invention, the most important image correction point is to make a white-colored region including tinted white stand out. Therefore, the intermediate region of the density correction curve may be a straight line for simplification of processing. . However, the intermediate region of the density correction curve may be represented by an optimum curve (multi-order curve) using a conventional algorithm.

  Further, according to the present invention for solving the above-described problems, a density correction curve generation module for a bridal photographed image obtained by photographing a bridal scene includes a density histogram generation unit that obtains a density histogram from the bridal photographed image, A highlight side saturated density value calculating unit that calculates a density value at which the ratio of the cumulative number of pixels from the highlight side of the density histogram to the total number of pixels is a first predetermined value as a highlight side saturated density value; and the bridal imaging A bridal image characteristic calculation unit that calculates a predetermined bridal image characteristic from an image; a saturation density value adjustment unit that adjusts the highlight-side saturation density value by an adjustment value calculated based on the bridal image characteristic; Concentration to generate a density correction curve using the highlighted saturation value as the highlight saturation point And a positive curve generating unit. The density correction curve generation module configured as described above is also accompanied by the operational effects described in the density correction curve generation method according to the present invention, and can include various additional characteristic configurations described above.

  The present invention also includes a density correction curve generation program for causing a computer to execute the above density correction curve generation method. Other features and advantages of the present invention will become apparent from the following description of embodiments using the drawings.

  The principle of the density correction curve generation technique according to the present invention will be described with reference to schematic diagrams. FIG. 1 shows a density (based on (R + G + B) / 3 in general) based on a pixel value obtained by integrating R, G, and B for a color image composed of an R color component, a G color component, and a B color component. The procedure of (luminance) value) is shown. First, an R, G, B density histogram is generated using density values of all pixels of the inputted bridal photographed image (# 01). The accumulated pixel number (frequency number) from the highlight side of the R, G, B density histogram: the total pixel number of Nh: the density value with respect to Z (%) is obtained as a first predetermined value: σ1, and this density is obtained. The value is the highlight side saturated density value: H (# 02). The first predetermined value: σ1 is determined in advance from a range of 1 to 20% according to the location of the wedding ceremony, the photographing apparatus used, the photographing illumination condition, and the like. Next, a cumulative pixel number (frequency number) from the shadow side of this R / G / B density histogram: the total pixel number of Ns: a density value with a ratio (%) to Z being a second predetermined value: σ 2 is obtained, This density value is set as the shadow side saturated density value: S (# 03). The second predetermined value: σ2 is determined to be smaller than the first predetermined value: σ1 in the range of 0.01 to 1%.

  Of the highlight-side saturation density value: H and the shadow-side saturation density value: S thus obtained, the highlight-side saturation density value: H is particularly important for bridal photography, and thus is obtained from the bridal photographed image. Is further adjusted based on predetermined image characteristics (referred to herein as bridal image characteristics) (# 04). Of course, the present invention does not exclude adjusting the shadow side saturation density value S based on the bridal image characteristics.

  Typical bridal image characteristics include bridal costume area: S (number of pixels) area ratio: S / Z in the entire area of the bridal image: Z (number of pixels). By detecting the face area of a person wearing a costume, narrowing down to the area below the face area, and combining the edge detection process and the specific color detection process, the process can be performed with considerably high accuracy. According to the knowledge based on a large number of sample images of the present inventor, the area-side ratio of the bridal costume region is up to about 20%, and the highlight-side saturation density value: H is shifted to the shadow side as the area ratio increases. Adjustment value: Δh is suitable, but if the area ratio of the bridal costume area exceeds 20%, the bridal costume itself becomes the most important subject. An adjustment value Δh that shifts the highlight side saturation density value H to the highlight side is suitable. The area ratio between the face area and the bridal costume area can be estimated from the area (number of pixels) of the face area. For this reason, an algorithm that directly obtains an adjustment value from the number of pixels in the face area may be employed.

  Another bridal image characteristic is the ratio of the number of pixels having a density value equal to or higher than a preset highlight threshold to the total number of pixels of the bridal photographed image. For example, in an 8-bit color image, if the ratio of the number of pixels having a density value of about 220 or more: R increases, reducing the gradation range on the highlight side makes the bright part of the image flat. Therefore, as the ratio increases, the adjustment value: Δh that shifts the highlight saturation value: H to the highlight side is calculated.

  After adjusting the highlight side saturation density value: H and the shadow side saturation density value: S using the adjustment value: Δh thus obtained, a density correction curve is generated (# 05). In this density correction curve, the shadow-side saturation density value: S is the shadow-side saturation point, so all input density values smaller than this become the minimum output density value (pure black) and the adjusted highlight-side saturation density value. : Since the position of H + Δh is the highlight side saturation point, all input density values larger than this become the maximum output density value (pure white). An intermediate region between the shadow side saturation point and the highlight side saturation point may be expressed by a straight line, but the shadow side saturation point and the highlight side saturation point are smoothly smoothed as an S-shaped curve based on image characteristics. It is also a suitable form to connect to. As a result, in the bridal photographed image, it is possible for the pure white bridal gown to output a photographic print reproduced in pure white regardless of various photographing conditions.

FIG. 2 shows a procedure for generating a density correction curve for each color component based on the pixel value of each color component for the color image to be corrected. Here, the procedure in FIG. This is done for each component.
First, an R density histogram (# 01r), a G density histogram (# 01g), and a B density histogram (# 01b) are generated using the density values of all pixels of the input bridal photographed image. The cumulative number of pixels from the highlight side of this R density histogram (frequency number): the total number of pixels of Nh_r: the density value with respect to Z (%) is the red component first predetermined value: σ1_r, and the density value is obtained. Red component highlight side saturation density value: Hr (# 02r). The red component first predetermined value: σ1_r, the green component first predetermined value: σ1_g, and the blue component first predetermined value: σ1_b are respectively 1 according to the location of the wedding ceremony, the photographing apparatus used, the photographing illumination conditions, and the like. It is determined in advance in a range of ˜20%. The red component first predetermined value: σ1_r, the green component first predetermined value: σ1_g, and the blue component first predetermined value: σ1_b may be the same or different.

  Similarly, the green component highlight side saturation density value: Hg is obtained using the G density histogram and the green component first predetermined value: σ1_g (# 02g), and the B density histogram and the blue component first predetermined value: σ1_b are used. Then, the blue component highlight side saturation density value: Hb is obtained (# 02b). Next, the density value from which the cumulative number of pixels from the shadow side of the R density histogram (frequency number): Ns_r total pixel number: ratio (%) to Z is the red component second predetermined value: σ2_r is obtained. Is the red component shadow side saturation density value: Sr (# 03r). Further, a density value in which the ratio (%) of the total number of pixels from the shadow side of the G density histogram (frequency number): Ns_g: Z to the green component second predetermined value: σ2_g is obtained, and this density value is obtained. Green component shadow side saturation density value: Sg (# 03 g). Further, a density value where the cumulative number of pixels from the shadow side of the B density histogram (frequency number): Ns_b total number of pixels: the ratio (%) to Z is the blue component second predetermined value: σ2_b is obtained, and this density value is obtained. Blue component shadow side saturation density value: Sb (# 03b). The second predetermined value: σ 2 (r, g, b) of each color component is set to a value smaller than the first predetermined value: σ 1 (r, g, b) in the range of 0.01 to 1%. .

  Here again, the highlight side saturation density value is adjusted using the adjustment values of the highlight side saturation density values: Δhr, Δhg, Δhb of each color component based on the bridal image characteristics as described above (# 04r) (# 04g) (# 04b).

  Next, a red component density correction curve is generated using the adjusted red component highlight side saturated density value: Hr + Δhr and the red component shadow side saturated density value: Sr (# 05r), and the adjusted green component highlight side saturated Density value: Hg + Δhg and green component shadow side saturation density value: Sg is used to generate a green component density correction curve (# 05g), and adjusted blue component highlight side saturation density value: Hb + Δhb and blue component shadow side saturation density Value: A blue component density correction curve is generated using Sb (# 05b). In each of these density correction curves, the position of the shadow side saturation density value becomes the shadow side saturation point, so all input density values smaller than this become the minimum output density value, and the position of the adjusted highlight side saturation density value: H + Δhr Becomes the highlight side saturation point, and all input density values larger than this become the maximum output density value. Accordingly, when the image data of each color component constituting the bridal photographed image is corrected by using the corresponding color component density correction curve, a pure white bridal gown is reproduced in pure white regardless of various photographing conditions. Can be output.

  An external view of a photographic printing apparatus incorporating the above-described density correction curve generation technique is shown in FIG. This photographic printing apparatus is a printing station 1B as a photographic printer that performs an exposure process and a development process on photographic paper P, and a photograph taken from an image input medium such as a developed photographic film 2a or a memory card 2b for a digital camera. Images (here, unless otherwise specifically required, the captured image data as digital data, and the captured image for printing and the captured image for monitor display based on the captured image data are simply referred to as a captured image) And an operation station 1A for generating / transferring print data used in the print station 1B.

  This photo printing apparatus is also called a digital minilab. As can be understood from FIG. 4, the printing station 1B pulls out the roll-shaped printing paper P stored in the two printing paper magazines 11 and prints it with the sheet cutter 12. The back print unit 13 prints print processing information such as color correction information and frame number on the back side of the photographic paper P, and the print exposure unit 14 cuts the print paper P into the size. A photographed image is exposed on the surface of the photographic paper P, and the exposed photographic paper P is sent to a processing tank unit 15 having a plurality of development processing tanks for development processing. After drying, the photographic paper P, that is, the photographic prints P, sent to the sorter 17 from the transverse feed conveyor 16 at the upper part of the apparatus is collected in a plurality of trays of the sorter 17 in a state of being sorted in order units (see FIG. 3) ).

  A photographic paper transport mechanism 18 is laid to transport the photographic paper P at a transport speed in accordance with various processes for the photographic paper P described above. The photographic paper transport mechanism 18 is composed of a plurality of nipping and transporting roller pairs including a chucker type photographic paper transport unit 18a disposed before and after the print exposure unit 14 in the photographic paper transport direction.

  The print exposure unit 14 applies R (red), G (green), and B (blue) to the printing paper P conveyed in the sub-scanning direction based on print data from the operation station 1A along the main scanning direction. A line exposure head for irradiating laser beams of the three primary colors (1) is provided. The processing tank unit 15 includes a color developing tank 15a for storing a color developing processing liquid, a bleach-fixing tank 15b for storing a bleach-fixing processing liquid, and a stabilizing tank 15c for storing a stable processing liquid.

  A film scanner 20 for obtaining photographed image data from photographed image frames of the photographic film 2a is arranged at the upper position of the desk-like console of the operation station 1A, and is used as a photographed image recording medium 2b mounted on a digital camera or the like. A media reader 21 that acquires captured images as image data from various semiconductor memories and CD-Rs that are used is incorporated in a general-purpose personal computer that functions as the controller 3 of the photographic printing apparatus. The general-purpose personal computer is also connected with a monitor 23 for displaying various types of information, and a keyboard 24 and a mouse 25 as pointing devices used as operation input units used for various settings and adjustments.

  The controller 3 of this photographic printing apparatus has a functional unit for performing various operations of the photographic printing apparatus using hardware and / or software, with the CPU as a core member, as shown in FIG. As described above, the functional unit particularly related to the present invention includes an image input unit 31 that captures a captured image read by the scanner 20 or the media reader 21 and performs preprocessing necessary for the next processing, and various windows. And a graphic user interface (hereinafter abbreviated as GUI) for generating a control command from a user operation input (via the keyboard 24, mouse 25, etc.) through the graphic operation screen. The GUI unit 33 to be constructed and the control command sent from the GUI unit 33 Density correction, color correction, photo retouch processing, and the like for the captured image transferred from the image input unit 31 to the memory 30 in order to generate desired print data based on an operation command input from the keyboard or directly from the keyboard 24 or the like. A video for displaying on the monitor 23 the graphic data sent from the GUI management unit 32, the simulated image as the print source image, the predicted finished print image, and the GUI unit 33 during the pre-judgment printing operation such as color correction. A video control unit 35 that generates a signal, a print data generation unit 36 that generates print data suitable for the print exposure unit 14 installed in the print station 1B based on processed image data that has undergone image processing, and a customer The original shot image and the image processed image are processed according to the request of Etc. formatter 37 that formats the format for writing the image as image data to the CD-R and the like.

  When the photographic image recording medium is the film 2a, the image input unit 31 separately sends the scan data for the pre-scan mode and the main scan mode to the memory 30, and performs preprocessing according to each purpose. When the captured image recording medium is the memory card 2b, when the captured image data includes thumbnail image data (low resolution data), this data is used for the purpose of displaying a list on the monitor 23. For this reason, the captured image is sent to the memory 30 separately from the main data (high resolution data), but if thumbnail image data is not included, a reduced image is created from the main data and sent to the memory 30 as low resolution image data.

  The image management unit 32 develops in the memory 30 a face detection module 40 that outputs face detection information including the position and size of the face area detected from the low-resolution captured image developed in the memory 30 using a face detection algorithm. A density correction module 50 that performs density correction on the high-resolution captured image, and a density correction curve that the density correction module 50 uses in density correction processing is appropriately based on the image characteristics of the captured image to be corrected. A density correction curve generation module 60 to be generated and an image processing module 70 that performs image processing such as color correction and filtering (blurring, sharpness, etc.) on the density-corrected captured image are provided.

  The face detection module 40 can use a general-purpose one. Here, based on a face detection algorithm, an area considered as a face in a photographed image is detected, and the face position and size (based on the face position) are detected. That output face detection information (such as the vertical and horizontal sizes of the rectangular pixel area). Many face detection algorithms for detecting a face from image data are known.

  The density correction curve generation module 60 includes a normal density correction curve generation module 60A that generates a density correction curve for a general photographed image using a known algorithm, and a bride wearing a pure white costume as a main subject. A bridal density correction curve generation module 60B for generating a density correction curve based on the basic principle described above for the bridal photographed image is included. In any case, the face detection information from the face detection module 40 is input so that the density correction curve can be adjusted according to the face size in the captured image.

  As shown in FIG. 6, the density correction module 50 stores the density correction curve set and adjusted by the density correction curve generation module 60 based on the image characteristics of the captured image as a table that can be accessed at high speed. 52 and a density correction unit 51 that executes density correction on a high-resolution captured image using the density correction curve table 52. Generally, the density correction unit 51 is realized by a program, and the density correction curve table 52 is realized by a data structure such as a lookup table. However, the present invention is not limited to such a configuration. Absent.

  Similarly, the density correction curve generation module 60 is also realized by a program. Among these, the bridal density correction curve generation module 60B particularly related to the present invention includes a density histogram generation unit 61, a highlight side saturation density value calculation unit 62, a shadow side saturation density value calculation unit 63, as shown in FIG. A bridal image characteristic calculation unit 64, a saturated density value adjustment unit 65, a bridal density correction curve generation unit (hereinafter simply referred to as a density correction curve generation unit) 66, and a basic density correction curve generation unit 67 are provided.

  The density histogram generation unit 61 obtains a density histogram for each color component (R, G, B) from the bridal photographed image developed in the memory 30, and the density value (pixel value, 0 to 255 in the case of 8-bit color). The number of pixels (frequency number) is obtained and temporarily stored.

  The highlight side saturated density value calculation unit 62 has a density value at which the ratio of the cumulative number of pixels from the highlight side of the density histogram for each color component obtained by the density histogram generation unit 61 to the total number of pixels is a first predetermined value. Is calculated as the highlight-side saturation density value. The first predetermined value: σ1 is set for each color component (red component first predetermined value: σ1_r, green component first predetermined value: σ1_g, blue component first predetermined value: σ1_b), and highlight side saturation density Value: H is also calculated for each color component (red component highlight side saturation density value: Hr, green component highlight side saturation density value: Hg, green component highlight side saturation density value: Hb). Similarly, the shadow side saturated density value calculation unit 63 has a ratio of the cumulative number of pixels from the shadow side of the density histogram for each color component obtained by the density histogram generation unit 61 to the total number of pixels smaller than the first predetermined value. The density value that becomes the set second predetermined value is calculated as the shadow side saturated density value. This second predetermined value: σ2 is also set for each color component (red component second predetermined value: σ2_r, green component second predetermined value: σ2_g, blue component second predetermined value: σ2_b), and the shadow side saturation density value : S is also calculated for each color component (red component shadow side saturation density value: Sr, green component shadow side saturation density value: Sg, blue component shadow side saturation density value: Sb). Each of the first predetermined values set for each color component is within a range of 1 to 20% and is determined in advance according to the location of the wedding ceremony, the photographing apparatus used, the photographing lighting conditions, etc., and the second predetermined value is It is determined in the range of 0.01 to 1% as necessary.

  The bridal image characteristic calculation unit 64 calculates the bridal image characteristic that is a parameter for adjusting the saturation density value directly obtained from the analysis of the density histogram. In this embodiment, as the bridal image characteristics, the ratio of the bridal costume area occupying the entire area of the bridal photographed image (the costume ratio), and a pixel having a density value equal to or higher than a preset highlight threshold with respect to the total number of pixels of the photographed image. A function for calculating a ratio of numbers (highlight ratio) is provided. If the face detection module 40 can detect the face from the bridal image, the costume ratio is calculated as the bridal image characteristic, and if the face cannot be detected, the highlight ratio is calculated as the bridal image characteristic. This is because the costume ratio is generally more suitable as a bridal image characteristic, and when a face is detected, it is relatively easy to detect the area of the pure white bridal costume by combining the edge detection algorithm and the white detection algorithm. This is because it can be possible. Of course, these two image characteristics may be used in combination.

  The saturation density value adjustment unit 65 has a function of adjusting the highlight side saturation density value calculated by the highlight side saturation density value calculation unit 62 based on the bridal image characteristics. When the bridal image characteristic calculation unit 61 obtains the ratio of the bridal costume area to the entire area of the photographed image as the bridal image characteristic, the adjustment value: Δh (r, g, b) (negative or positive value) is obtained from this ratio. Is adjusted in addition to the highlight side saturation density value: H. This adjustment value: Δh (r, g, b) is the lower the value of the saturation saturation value on the shadow side (the shadow side) as the ratio increases when the ratio of the bridal costume is less than the predetermined value (about ¼) However, if the ratio exceeds a predetermined value, the highlight saturation value is shifted to the highlight side as the ratio increases.

  When face detection by the face detection module 40 is not possible, the saturation density value adjustment unit 65 obtains the ratio of the number of pixels having a density value equal to or higher than the preset highlight threshold to the total number of pixels of the bridal captured image. As the ratio increases, the adjustment value that shifts the highlight saturation value to the higher value (highlight side): Δh (r, g, b) is calculated, and the highlight saturation value is calculated. adjust.

  When a table that directly extracts the size of the bridal costume area from the detected face area is prepared in advance, the bridal image characteristic calculation unit 64 uses a bridal that combines the edge detection algorithm and the white detection algorithm as described above. The costume area detection function can be omitted, and the number of pixels in the costume area can be calculated from the number of pixels in the face area.

  The density correction curve generation unit 66 generates a density correction curve using the adjusted highlight side saturation density value as the highlight side saturation point and the shadow side saturation density value as the shadow side saturation point. Since the reproducibility of a pure white wedding dress is extremely important for a bridal photographed image, the shape of the density correction curve in the intermediate region between the highlight side saturation point and the shadow side saturation point may be a normal straight line. However, in the case where neutral color correction is also necessary, the statistical representative value of the input captured image as in the past, for example, the minimum value, maximum value, and average value obtained from the histogram of the entire captured image are used as parameters. It is also possible to generate the final density correction curve by adopting the density correction curve shape in the intermediate region obtained from the basic density correction curve generation unit 67 that determines the shape of the density correction curve.

A typical processing flow of density correction curve generation by the bridal density correction curve generation module 60B as described above will be described with reference to the flowcharts of FIGS.
First, when the captured image to be corrected is related to a bridal scene, the mode is switched to the bridal correction mode through an initial setting screen (not shown) (# 10 Yes branch). If it is not a bridal scene, correction processing in the normal correction mode is performed (# 10 No branch). The density correction curve used in the normal correction mode is generated by the normal density correction curve generation module 60A, but the description of this process is omitted, and the correction process in the bridal correction mode will be described below.

  When the first bridal photographed image is input (# 12), the main routine for density correction curve creation starts. In this embodiment, this main routine is performed for each of the R, G, and B color components. A density histogram of the target captured image is generated for each color component (# 20). Subsequently, the first predetermined value: σ1 is set for each color component (# 22). The number of pixels (frequency value) is cumulatively calculated from the density value on the highlight side of the density histogram (# 24). This cumulative calculation is performed until the ratio of the cumulative number of pixels to the total number of pixels: Z exceeds the first predetermined value of the corresponding color component (# 26). The density value when the ratio of the total number of pixels: Z to the first predetermined value exceeds the first predetermined value is calculated as the highlight-side saturated density value of the corresponding color component, and is passed to the saturated density value adjusting unit 65 (# 28). ).

  Next, a process for calculating bridal image characteristics from the bridal photographed image to be corrected is performed (# 50). In the bridal image characteristic calculation processing routine shown in FIG. 8, first, face detection processing by the face detection module 40 is performed on the inputted bridal photographed image (# 51). When a face is detected in the face detection process (# 52 Yes branch), the costume area of the person having the face is obtained based on the face detection information received by the bridal image characteristic calculation unit 64, and the ratio of the costume area to the entire area Is calculated (# 53). Next, an adjustment value: Δh (r, g, b) is determined from the ratio of the costume area occupied by the saturated density value adjustment unit 65 in the entire area. When a face is not detected in the face detection process (# 52 No branch), the bridal image characteristic calculation unit 64 sets a predetermined highlight threshold (# 55), and sets the number of pixels having a density value equal to or higher than the highlight threshold. The ratio to the total number of pixels is calculated (# 56). Next, an adjustment value: Δh (r, g, b) is determined from the ratio of the number of pixels having a density value equal to or higher than the highlight threshold in the total number of pixels (# 57).

  In the flowchart of FIG. 8, the ratio of the costume area is calculated and the adjustment value is determined only when the face is detected by the face detection process. However, even if face detection cannot be performed, the bridal costume is changed depending on the color and shape. If the area can be estimated, a flow for calculating the ratio of the costume area from the estimated costume area and determining the adjustment value may be added.

  In any case, when the adjustment value is determined, the saturation density value adjustment unit 65 is calculated by the highlight side saturation density value calculation unit 62 using these adjustment values: Δh (r, g, b). Highlight side saturation density value: H is adjusted (# 29).

  Next, a second predetermined value: σ2 is set for each color component (# 30). The number of pixels (frequency value) is cumulatively calculated from the density value on the shadow side of the density histogram (# 32). This cumulative calculation is performed until the ratio of the cumulative number of pixels to the total number of pixels: Z exceeds the second predetermined value of the corresponding color component (# 34). The density value when the ratio of the cumulative number of pixels to Z: the second predetermined value exceeds the second predetermined value is calculated as the shadow-side saturated density value of the corresponding color component, and is passed to the saturated density value adjusting unit 65 (# 36). . If the shadow-side saturation density is also adjusted based on the above-described bridal image characteristics, it is adjusted here (# 37), but this step can be omitted.

  The adjusted highlight-side saturation density value and the shadow-side saturation density value not adjusted in this embodiment are used as the highlight-side saturation point and the shadow-side saturation point, respectively, and the intermediate area is a straight line (of course, the basic density correction curve generation unit) A density correction curve is generated (# 38). The generated density correction curve data is sent from the density correction curve generation unit 66 to the density correction curve table 52 of the density correction module 50, where it is tabulated so that it can be accessed at high speed (# 40). The density correction unit 51 performs density correction on the bridal photographed image to be corrected developed in the memory 30 while using this density correction curve table 52 (# 42). The above-described density correction is performed on all the input bridal images (# 44).

  In the above-described embodiment, creation of a density histogram, setting of first and second predetermined values, calculation of highlight-side saturation density values, calculation of shadow-side saturation density values, calculation of bridal image characteristics and determination of adjustment values, etc. This processing was performed for each color component to generate a density correction curve for each color component, and image correction was performed, but each color component was averaged using the average value of each color component, etc. Alternatively, the density correction curve may be generated to perform density correction.

  Further, the print station 1B exposes a photographed image to the photographic paper P by a print exposure unit 14 equipped with an exposure engine, and a so-called silver salt photographic printing system in which the photographic paper P after the exposure is subjected to a plurality of development processes. Of course, the print station 1B using the density correction curve determination technique according to the present invention is not limited to such a method. For example, an image is ejected onto a film or paper to eject an image. Various photographic printing methods such as an inkjet printing method for forming a film and a thermal transfer method using a thermal transfer sheet can be employed. Further, the bridal density correction curve generation technique according to the present invention may be mounted on a self-type photographic printing apparatus such as a kiosk terminal.

Schematic diagram showing the basic principle of the technique according to the present invention for generating a density correction curve common to each color component Schematic diagram showing the basic principle of the technique according to the present invention for generating a density correction curve for each color component External view of photographic printing apparatus employing density correction curve generation technology according to the present invention Schematic diagram schematically showing the configuration of the print station of the photo printing device Functional block diagram explaining the functional elements built in the controller of the photo printing device Functional block diagram showing the functional configuration of the density correction curve generation module Flowchart showing the flow of processing in one embodiment of the density correction curve generation module Flow chart showing bridal image characteristic calculation routine

Explanation of symbols

30: Memory 40: Face detection module 50: Density correction module 51: Density correction unit 52: Density correction curve table 60: Density correction curve generation module 60A: Normal density correction curve generation module 60B: Bridal density correction curve generation module (density correction) Curve generation module)
61: density histogram generation unit 62: highlight side saturation density value calculation unit 63: shadow side saturation density value calculation unit 64: bridal image characteristic calculation unit 65: saturation density value adjustment unit 66: density correction curve generation unit 67: basic density Correction curve generator

Claims (8)

In a method for generating a density correction curve for a bridal photographed image obtained by photographing a bridal scene,
Obtaining a density histogram from the bridal image;
Calculating a density value at which a ratio of the cumulative number of pixels from the highlight side of the density histogram to the total number of pixels is a first predetermined value as a highlight side saturated density value;
Adjusting the highlight-side saturation density value by an adjustment value calculated based on a predetermined bridal image characteristic of the bridal captured image;
Generating a density correction curve using the adjusted highlight side saturation density value as a highlight side saturation point; and
A density correction curve generation method comprising:   Calculating a density value at which the ratio of the cumulative number of pixels from the shadow side of the density histogram to the total number of pixels is a second predetermined value as a shadow side saturated density value; and using the shadow side saturated density value as the bridal image characteristic 2. The method according to claim 1, further comprising a step of adjusting according to an adjustment value calculated based on the correction value, wherein the density correction curve is modified using the adjusted shadow side saturation density value as a shadow side saturation point. Density correction curve generation method.   The density correction curve generation method according to claim 1, wherein the bridal image characteristic is a ratio of a bridal costume region in an entire region of the photographed image.   The density correction curve generation method according to claim 1, wherein the bridal image characteristic is a ratio of a face area to an entire area of the photographed image.   3. The density correction curve generation method according to claim 1, wherein the bridal image characteristic is a ratio of the number of pixels having a density value equal to or higher than a preset highlight threshold to the total number of pixels of the photographed image. .   The density correction curve generation method according to claim 1, wherein the density correction curve is created for each color component.   The density correction curve generation method according to claim 1, wherein the density correction curve is set to be a straight line in an intermediate region thereof. In the density correction curve generation module for the bridal photographed image obtained by photographing the bridal scene,
A density histogram generation unit for obtaining a density histogram from the bridal photographed image;
A highlight side saturated density value calculating unit that calculates a density value at which a ratio of the cumulative number of pixels from the highlight side of the density histogram to the total number of pixels is a first predetermined value as a highlight side saturated density value;
A bridal image characteristic calculation unit for calculating a predetermined bridal image characteristic from the bridal photographed image;
A saturation density value adjustment unit for adjusting the highlight side saturation density value by an adjustment value calculated based on the bridal image characteristics;
A density correction curve generation unit that generates a density correction curve using the adjusted highlight side saturation density value as a highlight side saturation point;
A density correction curve generation module comprising:

Images