JP2009044258A - Image processing apparatus, image data generation method, and computer program - Google Patents

Abstract

An object of the present invention is to provide a technique for shortening the processing time when changing the size, resolution, contrast, brightness, etc. of an image.
A computer 100 includes an image data acquisition unit 162 that acquires first image data representing an image, an interpolation function derivation unit 166 that derives a cubic interpolation function for performing cubic interpolation processing, and an image. In order to enlarge, a third-order interpolation processing unit 164 that performs third-order interpolation processing on the first image data using the derived third-order interpolation function, and output image data including interpolation pixels are generated. The coefficient of the cubic interpolation function is expressed as a function of the coefficient of the adjustment function indicating the input / output characteristics when adjusting the contrast of the image.
[Selection] Figure 1

Description

  The present invention relates to an image processing apparatus capable of performing cubic interpolation processing on image data.

  Conventionally, for example, when an image is enlarged and brightness, contrast, and sharpness are adjusted on a computer, the image data indicating the image is subjected to enlargement processing, and then the brightness adjustment and contrast adjustment are performed. The sharpness was adjusted sequentially. Then, the number of pixels × 3 (for each pixel of R, G, and B) needs to be read from the memory and written to the memory for one type of processing (for example, enlargement processing). For this reason, there has been a problem that the processing time when performing processing such as enlargement is long, and it takes time to display on a display or to print with a printer. The same problem occurs when the image is reduced or the resolution of the image is changed.

  Therefore, in order to shorten the processing time, when enlarging or reducing the image, an interpolation operation method combining B-spline interpolation and cubic spline interpolation is used to enlarge and reduce the image and sharpen the image. A method of adjusting the degree has been proposed (see, for example, Patent Document 1).

JP-A-9-93426

  According to the above-described interpolation calculation method, the sharpness is adjusted when performing processing such as image enlargement, so that the processing is faster than the conventional method. However, in the case of adjusting brightness and adjusting contrast, after processing such as enlargement, the brightness and contrast are sequentially adjusted. It took.

  Such a problem is a problem common to image processing apparatuses such as printers, personal computers, and digital cameras that can change the size, resolution, sharpness, contrast, brightness, and the like of an image.

  Therefore, an object of the present invention is to provide a technique for shortening the processing time when changing the size, resolution, contrast, brightness, and the like of an image.

  SUMMARY An advantage of some aspects of the invention is to solve at least a part of the problems described above, and the invention can be implemented as the following forms or application examples.

Application Example 1 An image processing apparatus,
An image data acquisition unit for acquiring first image data indicating an image;
A cubic interpolation function derivation unit for deriving a cubic interpolation function to be used when performing cubic interpolation processing on the first image data;
In order to change at least one of the size and resolution of the image, a second interpolation process is performed on the first image data using the derived third-order interpolation function to perform a second interpolation process. An image data generation unit for generating and outputting the image data;
With
The image processing apparatus, wherein the coefficient of the cubic interpolation function is expressed as a function of a coefficient included in an adjustment function indicating input / output characteristics when adjusting the contrast of the image.

  According to the image processing apparatus of Application Example 1, the coefficient of the cubic interpolation function is a function of a coefficient included in the adjustment function indicating the input / output characteristics when adjusting the contrast of the image. The cubic interpolation function is also different. That is, by performing a cubic interpolation process on the first image data using the derived cubic interpolation function, the image size is changed (that is, the image is enlarged or reduced), and the image resolution is increased. In addition, the contrast can be adjusted.

  Therefore, it is possible to shorten the processing time when performing processing for changing the size and resolution of an image and adjustment of contrast. For example, it is possible to shorten the time until the preview image after image enlargement and contrast adjustment is displayed.

Application Example 2 In the image processing apparatus according to Application Example 1,
The cubic interpolation process is:
It is a process of adding a constant of an adjustment function indicating an input / output characteristic when adjusting the brightness of the image to a result obtained by multiplying the first image data by the cubic interpolation function. An image processing apparatus.

  According to the image processing apparatus of the application example 2, the image can be enlarged and the contrast and brightness can be adjusted. Therefore, the processing time can be further shortened.

Application Example 3 In the image processing apparatus according to Application Example 1 or 2,
The cubic interpolation function deriving unit
An image processing apparatus, wherein the cubic interpolation function is derived so that the second image data shows a predetermined sharpness.

  According to the image processing apparatus of the application example 2, when performing processing such as image enlargement, the sharpness can be adjusted at the same time, so that the processing time can be further shortened.

  The present invention is not limited to the above-described aspect of the image processing apparatus, but as an aspect as a computer program for constructing the image processing apparatus, an aspect as a storage medium storing the computer program, and an image data generation method It is also possible to implement in various modes such as the above mode.

A1. Example configuration:
FIG. 1 is a block diagram showing a computer 100 as an embodiment of the present invention. The computer 100 includes a CPU 110 for performing various processes and controls according to a computer program, an internal memory 120 such as a ROM and a RAM, a peripheral for communicating with a scanner 200, a digital camera, a drive such as an HDD and a CD, and the like. A device interface 130, an external memory interface 140 for reading data stored in the removable memory 300, a display 150 including an LCD for displaying images and the like, and a bus 170 connecting these components are provided.

  The internal memory 120 stores a computer program that functions as the image processing unit 160. Note that the function of the image processing unit 160 is realized by the CPU 110 executing a computer program. This computer program is provided in a form recorded on a ROM chip (not shown). Further, instead of using such a ROM, a computer program may be read by a CD-ROM drive device (not shown) and written in a nonvolatile RAM. Note that a sharpness LUT (Look Up Table) 122, a contrast LUT 124, and a brightness LUT 126, which will be described later, are also stored in the ROM together with a computer program for image processing.

  The image processing unit 160 includes an image data acquisition unit 162, a cubic interpolation processing unit 164, an interpolation function derivation unit 166, and an image data output unit 168. The image data acquisition unit 162 acquires image data via the peripheral device interface 130 and the external memory interface 140 and stores the acquired image data in the internal memory 120. The cubic interpolation processing unit 164 performs a cubic interpolation process on the image data stored in the internal memory 120 using the cubic interpolation function obtained by the interpolation function deriving unit 166 described later, and obtains it. The density of the interpolated pixel is obtained by simultaneously performing processing such as enlargement / reduction of the image, resolution conversion, etc., and adjustment of sharpness, contrast, and brightness. The interpolation function deriving unit 166 derives a cubic interpolation function based on the sharpness and contrast designated by the user (detailed later). The image data output unit 168 generates output image data including the interpolation pixel obtained by the cubic interpolation processing unit 164 and causes the display 150 to display the output image data.

  In the present embodiment, the case where the image data for output is displayed on the display 150 is illustrated, but it can be output to various output devices such as output to a printer or writing to a hard disk. For example, when sending to a printer, the image data output unit 168 may generate print image data suitable for printing by the printer based on the output image data, and send it to the printer.

  The interpolation function deriving unit 166 in this embodiment corresponds to the cubic interpolation function deriving unit in the claims, and the cubic interpolation processing unit 164 and the image data output unit 168 correspond to the image data generating unit in the claims.

A2.3 cubic interpolation function:
A2.1. Bicubic method:
In general, when changing the size or resolution of an image, if there is no corresponding pixel, interpolation is performed. As interpolation methods, the nearest neighbor method (also referred to as nearest neighbor method), which is represented by nearby points, the bilinear method (also referred to as bilinear interpolation) that takes a weighted average according to the distance to nearby points, and 16 surrounding points There is a bicubic method (also called bicubic interpolation) calculated from

  The bicubic method has the least loss of original image information as compared with the near-less neighbor method and the bilinear method, and a natural image can be obtained even after the interpolation method is applied, but the calculation amount is large and the processing speed is slow. Here, a method of interpolating pixels by the bicubic method will be briefly described with reference to FIG. FIG. 4 is an explanatory diagram for explaining a calculation method in the case of interpolating pixels by the bicubic method.

  In order to simplify the description, the case of one-dimensional (for example, the case of enlarging only horizontally) will be described as an example. In the one-dimensional case, the density (luminance, gradation value) of the interpolation pixel is obtained with reference to four pixels of the original image close to the interpolation pixel. Specifically, [Density of original image pixel (hereinafter also referred to as reference pixel)] × [Weight function k (x) according to distance between reference pixel and interpolation pixel] is calculated for each of four reference pixels. By obtaining the sum, the density of the interpolated pixel can be obtained. This weight function k (x) is called a cubic interpolation function. x is the distance between the interpolated pixel and the reference pixel to be calculated when the distance between adjacent reference pixels is 1.

  For example, Equation (1) using parameters B and C is known, where k (x) is a cubic interpolation function when interpolation is performed using the bicubic method. Expression (1) is an expression called BC spline expression.

For example, in the case where the original image is enlarged three times, a case where the density of the interpolation pixel is obtained by the bicubic method will be described with reference to FIG. When the density of the pixel P _u in the position u of the original image and f (u), adjacent pixels _{P u-1, P u +} 1 concentration respectively f (u-1), the f (u + 1). FIG. 4A is an explanatory diagram for explaining an image in which the original image is enlarged three times. As shown in the figure, when the image is enlarged three times, at the same resolution, two pixels P _{u + 1/3} and P _{u + 2/3} are interpolated between the pixel P _u and the pixel P _{u + 1.} Must. FIG. 4B is an explanatory diagram showing the distance x between the reference pixel and the interpolation pixel that are referred to when the density f (u + _1/3 ) of the interpolation pixel P _{u + 1/3} is obtained.

As described above, the density of the pixel P _{u + 1/3} can be obtained by adding the value obtained by multiplying the density of the reference pixel by the cubic interpolation function k (x). Formula (2) shows a calculation formula for obtaining the density f (u + 1/3) of the interpolation pixel P _{u + 1/3} .

  f (u + 1/3) = f (u−1) × k (3/4) + f (u) × k (1/3) + f (u + 1) × k (2/3) + f (u + 2) × k (5 / 3) (2)

  In the two-dimensional case (enlarged vertically and horizontally), as described above, after horizontally enlarging, the pixels can be obtained by similarly enlarging vertically. That is, 16 pixels of 4 vertical pixels × 4 horizontal pixels are referred to.

A2.2. Sharpness adjustment:
When changing the size and resolution of the image, the sharpness can be changed at the same time. For example, when Expression (1) is used as the cubic interpolation function k (x), the sharpness of the image can be adjusted by changing the values of B and C in Expression (1). For example, when C = 0 and B is increased, a blurred image with low sharpness is obtained. FIG. 5 is an explanatory diagram showing frequency characteristics when parameters B = 0.5 and C = 0, and FIG. 6 is an explanatory diagram showing frequency characteristics when parameters B = 1.0 and C = 0. As shown in the figure, high frequency components can be cut by increasing B. That is, if the value of B is reduced, the image can be sharpened, and if the value of B is increased, the image can be smoothed.

A2.3. Contrast adjustment:
FIG. 7 is an explanatory diagram showing the input / output characteristics used when adjusting the contrast. For example, as described in A2.1, when obtaining the density of the interpolation pixel, the distance between the obtained interpolation pixel and the reference pixel is x, the density of the reference pixel is l, and the density of the reference pixel is the cubic interpolation function k (x ) Is h (x), and the cubic interpolation function k (x) = a | x | ³ + b | x | ² + c | x | + d, h (x) is as follows: Become.

h (x) = (a | x | ³ + b | x | ² + c | x | + d) l (3)

  Contrast conversion is performed for h (x) so as to show the input / output characteristics shown in FIG. Assuming that the result of contrast conversion is t (x), the result is as follows.

とし、式（４）に、式（３）を代入すると、
ｔ（ｘ）＝（ａ｜ｘ｜³＋ｂ｜ｘ｜²＋ｃ｜ｘ｜＋ｄ）αl+β＝（ａα｜ｘ｜³＋ｂα｜ｘ｜²＋ｃα｜ｘ｜＋ｄα）l+β
となる。
ａα＝ａ１、ｂα＝ｂ１、ｃα＝ｃ１、ｄα＝ｄ１とすると、３次補間関数ｋ１（ｘ）は、以下のようになる。 here,

And substituting equation (3) into equation (4),
t (x) = (a | x | 3 + b | x | 2 + c | x | + d) αl + β = (aα | x | 3 + bα | x | 2 + cα | x | + dα) l + β
It becomes.
When aα = a1, bα = b1, cα = c1, and dα = d1, the cubic interpolation function k1 (x) is as follows.

k1 (x) = a1 | x | ³ + b1 | x | ² + c1 | x | + d1 (5)

  As described above, the coefficients of the cubic interpolation function are set to a1, b1, c1, and d1. If the interpolation pixel is obtained by adding the result obtained by multiplying the density of each reference pixel by the cubic interpolation function and further adding β, the contrast can be changed at the same time as the image is enlarged. In the case of enlarging / reducing in the vertical and horizontal directions, if the above-described coefficients are used in both the vertical and horizontal directions, the contrast conversion is doubled.

A2.4. Brightness adjustment:
FIG. 8 is an explanatory diagram showing input / output characteristics used when adjusting the brightness. FIG. 8 shows input / output characteristics when the entire image is uniformly brightened by v.

If the input is in and the output is out,
out = in + v (6)

  The brightness can be adjusted by substituting the density of the interpolated pixel subjected to the contrast adjustment processing as an input value into Expression (6). Note that in an image in which the density of one pixel is expressed by 0 to 255, the density of the interpolation pixel is usually limited to 255 when the density is 255 or higher, and 0 when the density is 0 or lower. However, when the brightness is increased by v, the density is limited to 0 to 255 + v when v> 0, v to 255, and v <0.

Substituting the result t (x) obtained by performing the contrast adjustment process into equation (6),
out = t (x) + v = (a1 | x | 3 + b1 | x | 2 + c1 | x | + d1) l + β + v = k1 (x) l + v1, v1 = β + v ··· (7)

  In this way, the coefficients of the cubic interpolation function k1 (x) are set as a1, b1, c1, and d1, and the result obtained by multiplying each reference pixel by the cubic interpolation function is added, and v1 is added to obtain the interpolation pixel. If required, the image can be enlarged and the contrast and brightness can be changed.

A2.5. How to determine the density of interpolated pixels:
By obtaining a1, b1, c1, d1, and v1 in Expression (7) as follows, coefficients relating to sharpness and contrast adjustment can be included in the coefficients of the cubic interpolation function. When obtaining the density of the interpolation pixel using the bicubic method, the result obtained by multiplying each reference pixel of the original image by the above-described cubic interpolation function is added, and if v1 is added, the image is enlarged. The sharpness, contrast and brightness can be changed.

a1 to d1 are obtained by the following formulas that vary depending on the range of x.
(I) When | x | <1 a1 = aα = (12−9B−6C) α × 1/6 (11)
b1 = bα = (− 18 + 12B + 6C) α × 1/6 (12)
c1 = cα = 0 × α × 1/6 = 0 (13)
d1 = dα = (6-2B) α × 1/6 (14)
(Ii) When 1 ≦ | x | <2 a1 = aα = (− B−6C) α × 1/6 (21)
b1 = bα = (6B + 30C) α × 1/6 (22)
c1 = cα = (− 12B−48C) α × 1/6 (23)
d1 = dα = (8B + 24C) α × 1/6 (24)
(Iii) When | x | ≧ 2 a1 = b1 = c1 = d1 = 0 (31)

v1 is obtained as follows regardless of the range of x.
v1 = β + v (41)

  As can be seen from the above equations (11) to (24), each coefficient of the cubic interpolation function includes constants B and C relating to the sharpness adjustment and a coefficient α relating to the contrast adjustment. That is, the coefficient of the cubic interpolation function is expressed as a function of B, C, and α. Further, v1 includes a constant β related to contrast adjustment and a constant v related to brightness adjustment. Therefore, as described above, the coefficient of the cubic interpolation function is obtained, and the density of the interpolation pixel is obtained by using the cubic interpolation function and v1, thereby enlarging the image, and sharpness, contrast, and brightness. Can be changed.

  As described above, α and β can be obtained from n and m in the input / output characteristics of contrast conversion. In this embodiment, the contrast LUT 124 describes the values of α and β with respect to the contrast strength (%) described later. The sharpness LUT 122 describes B and C values with respect to a sharpness value described later. The brightness LUT 126 describes the value of v with respect to brightness (%). Therefore, B, C, α, β, and v can be obtained by referring to each LUT based on the sharpness, contrast, and brightness input by the user.

A3. Example operation:
FIG. 2 is a flowchart showing the flow of image processing in the computer 100 of this embodiment.

  When the computer 100 is activated, if the user inserts the removable memory 300 into a card slot (not shown) of the computer 100 and the removable memory 300 is connected to the external memory interface 140, the CPU 110 Recognizes the memory 300. Then, the CPU 110 functions as an application by reading and executing the application program stored in the internal memory 120. When the application starts up, an image stored in the removable memory 300 is displayed. When the user selects “image processing” (not shown) from the menu, the CPU 110 functions as an image processing unit by reading and executing a computer program for image processing. Then, as shown in FIG. 3, various types of executable image processing are displayed.

  FIG. 3 is an explanatory diagram showing the image processing screen W. The image processing screen W is provided with an enlargement ratio input field cl1, a sharpness input field cl2, a contrast input field cl3, and a brightness input field cl4. These input fields are configured such that the user selects and inputs an up / down button. Further, various buttons such as an “OK” button B1 for confirming various contents set by the user are provided.

  In the present embodiment, 100% (not enlarged), 200%, 400%, 600%, and 800% can be selected as the enlargement ratio. Sharpness can be selected from -20%, -10%, 0% (standard), + 10%, and + 20%. With 0% as the standard, a negative value means smoothing the image, and a positive value means sharpening the image. Similarly, the contrast and brightness can be selected from -20%, -10%, 0% (standard), + 10%, and + 20%. The display of sharpness or the like is not limited to% display. For example, in the case of sharpness, a display such as NO (standard), Low (slightly sharp), or High (sharp) may be used.

  When the user inputs each value of enlargement, sharpness, contrast, and brightness on the image processing screen W and selects the button B1, the application acquires the input information, and enlargement rate information, sharpness information, The contrast information and the brightness information are stored in the internal memory 120, and the image processing screen W is closed.

  The interpolation function deriving unit 166 refers to the sharpness LUT 122 and obtains the above B and C values based on the sharpness information stored in the internal memory 120 (FIG. 2: step S102). Subsequently, the interpolation function deriving unit 166 determines α and β based on the contrast information with reference to the contrast LUT 124 (step S104). Then, the interpolation function deriving unit 166 refers to the lightness LUT 126 and obtains v based on the lightness information (step S106). The interpolation function deriving unit 166 obtains the above-described a1, b1, c1, d1, and v1 using the values of B, C, α, β, and v (step S108).

  The image data acquisition unit 162 acquires image data stored in the removable memory 300 via the external memory interface 140, and stores the acquired image data in the internal memory 120 (step S110). The cubic interpolation processing unit 164 refers to each pixel of the image data stored in the internal memory 120 and derives a cubic interpolation function derived based on the enlargement ratio information stored in the internal memory 120, and The density of each interpolation pixel is obtained using v1 (step S111). The image data output unit 168 generates output image data including the interpolated pixels and displays it on the display 150 (step S112).

  Steps S102 to S108 in this embodiment correspond to step (b) in the claims, step S110 corresponds to step (a) in the claims, and steps S111 and 112 correspond to step (c) in the claims.

A4. Effects of the embodiment:
As described above, according to the computer 100 of the present embodiment, sharpness, contrast, and brightness can be adjusted simultaneously when enlarging an image. Therefore, the amount of access to the memory when performing these adjustments to generate image data can be reduced, and the processing can be speeded up. For example, when a preview image such as enlargement / reduction is displayed, it is possible to shorten the time until the preview image is displayed.

B. Modifications The present invention is not limited to the above-described embodiments, and can be implemented in various modes without departing from the scope of the invention.

  (1) In the above-described embodiment, the interpolation function deriving unit 166 obtains B, C, α, β, and v by referring to each LUT based on the sharpness or the like input by the user, and sets the value as the value. Based on the above, it has been shown that a cubic interpolation function is derived. For example, an LUT in which a coefficient of a cubic interpolation function corresponding to a combination of sharpness and the like input by a user is prepared in advance. You may make it obtain | require with reference to LUT. By doing so, the processing can be further speeded up.

  (2) In the above-described embodiments, the computer 100 is shown as the image processing apparatus. However, the image size, resolution, sharpness, contrast, brightness, etc., can be changed using a printer, digital camera, photo storage, or the like. Any image processing apparatus capable of supporting the

  (3) In the above-described embodiments, the case of enlarging the image has been illustrated. However, when the image is reduced, the resolution is changed, etc., the sharpness, contrast, and brightness may be adjusted at the same time. . Further, instead of adjusting all of them at the same time, either the contrast or the brightness may be adjusted when changing the size or resolution of the image. Even if it does in this way, processing speed can be made faster compared with the case where each processing is performed separately.

It is a block diagram which shows the computer 100 as one Example of this invention. It is a flowchart which shows the flow of the image processing in the computer 100 of a present Example. It is explanatory drawing which shows the image processing screen. It is explanatory drawing for demonstrating the calculation method in the case of interpolating a pixel by the bicubic method. It is explanatory drawing which shows the frequency characteristic in case parameters B = 0.5 and C = 0. It is explanatory drawing which shows the frequency characteristic in case parameters B = 1.0 and C = 0. It is explanatory drawing which shows the input-output characteristic used when adjusting contrast. It is explanatory drawing which shows the input / output characteristic used when adjusting brightness.

Explanation of symbols

100 ... Computer 110 ... CPU
DESCRIPTION OF SYMBOLS 120 ... Internal memory 130 ... Peripheral device interface 140 ... External memory interface 150 ... Display 160 ... Image processing part 162 ... Image data acquisition part 166 ... Interpolation function deriving part 168 ... Image data output part 170 ... Bus 200 ... Scanner 300 ... Removable memory 122 ... Sharpness LUT
124 ... Contrast LUT
126 ... Lightness LUT
W ... Image processing screen B1 ... Button cl1 ... Enlargement rate input field cl2 ... Sharpness input field cl3 ... Contrast input field cl4 ... Brightness input field

Claims (5)

An image processing apparatus,
An image data acquisition unit for acquiring first image data indicating an image;
A cubic interpolation function derivation unit for deriving a cubic interpolation function to be used when performing cubic interpolation processing on the first image data;
In order to change at least one of the size and resolution of the image, a second interpolation process is performed on the first image data using the derived third-order interpolation function to perform a second interpolation process. An image data generation unit for generating and outputting the image data;
With
The image processing apparatus, wherein the coefficient of the cubic interpolation function is expressed as a function of a coefficient included in an adjustment function indicating input / output characteristics when adjusting the contrast of the image. The image processing apparatus according to claim 1,
The cubic interpolation process is:
It is a process of adding a constant of an adjustment function indicating an input / output characteristic when adjusting the brightness of the image to a result obtained by multiplying the first image data by the cubic interpolation function. An image processing apparatus. The image processing apparatus according to claim 1, wherein:
The cubic interpolation function deriving unit
An image processing apparatus, wherein the cubic interpolation function is derived so that the second image data shows a predetermined sharpness. An image data generation method for generating second image data by performing cubic interpolation processing on first image data representing an image in order to change at least one of the size and resolution of the image. And
(A) obtaining the first image data;
(B) deriving a cubic interpolation function for performing the cubic interpolation process;
(C) Using the cubic interpolation function derived in the step (b), the cubic interpolation processing is performed on the first image data acquired in the step (a) to perform the first interpolation. Generating and outputting the image data of 2; and
With
The method of generating image data, wherein the coefficient of the cubic interpolation function is expressed as a function of a coefficient included in an adjustment function indicating input / output characteristics when adjusting the contrast of the image. A computer program for generating a second image data by performing a cubic interpolation process on the first image data representing an image in order to change at least one of the size and resolution of the image. And
A function of acquiring the first image data;
Deriving the cubic interpolation function, wherein the coefficient of the cubic interpolation function for performing the cubic interpolation process is expressed as a function of a coefficient of an adjustment function indicating input / output characteristics when adjusting the contrast of the image. Function to
A function of performing a third-order interpolation process on the acquired first image data using the derived third-order interpolation function to generate and output the second image data;
A computer program for causing a computer to realize the above.

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