JP2010193384A - Image processing apparatus, method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To control the degree of noise reduction of a tone conversion processed image, based on image property, and/or tone conversion characteristic, brightness information and edge information of the image. <P>SOLUTION: An image processing apparatus includes: a tone conversion characteristic calculation portion 104 which divides an input image into a plurality of areas, and calculates a first tone conversion characteristic for this every area; a tone conversion characteristic processing portion 105 which performs tone conversion characteristic processing using the first tone conversion characteristic calculated by the tone conversion characteristic calculation portion 104; a noise reduction control property calculation portion 106 which calculates a noise reduction control property for adjusting the degree of noise reduction processing based on the first tone conversion characteristic and/or the property of the image calculated by the tone conversion characteristic calculation portion 104; and a noise reduction processing portion 107 which performs noise reduction processing to the input image processed by the tone conversion characteristic processing portion 105 based on the noise reduction control property. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image processing apparatus, and more particularly to an image processing apparatus, method, and program for performing noise reduction processing on an image that has been subjected to gradation conversion processing having different characteristics in each region obtained by dividing the image.

  Conventionally, in order to widen the dynamic range of an input image, a space variant gradation conversion process is performed in which gradation conversion characteristics are changed for each area of the input image. FIG. 18 is a block diagram of noise reduction processing using a conventional space variant tone conversion characteristic. In FIG. 18, when an image is input to the gradation conversion processing unit, gradation conversion processing is performed based on the space variant gradation conversion characteristics calculated from the input image. In addition, the image subjected to the space variant tone conversion processing is subjected to noise reduction processing using the space variant tone conversion characteristics as they are.

JP 2007-31331 A JP 2006-50042 A

  However, in the conventional method of performing noise reduction processing using the space-variant tone conversion characteristics as they are, noise reduction cannot be performed for each area of the image in order to reduce noise with a uniform intensity over the entire image. There was a problem. For example, an adjustment that significantly reduces noise only in a specific area, such as reducing only the area where the noise is conspicuous and the area where the noise is greatly amplified by the tone conversion process is stronger than other areas. Can not do.

  Therefore, when priority is given to enhancing the noise reduction effect, a strong noise reduction process is uniformly applied to the entire image, resulting in a problem that the resolution of the entire image is deteriorated. On the other hand, when priority is given to maintaining a sense of resolution in the entire image, there is a problem that noise remains in the entire image.

  FIG. 19 conceptually shows a noise reduction processing method using the conventional space variant tone conversion characteristics as they are. In FIG. 19, noise reduction processing is performed on a space variant tone-converted image with priority given to maintaining a sense of resolution. For this reason, in the image 4 of FIG. 19 that is an image after the space variant tone conversion and noise reduction processing, there is a white point that indicates a region including noise throughout the entire image, and noise remains in the entire image. You can see that

  The present invention has been made to solve the above-described problem. An image processing apparatus and an image processing method capable of significantly reducing noise in a region where noise is conspicuous and maintaining a sense of resolution in a region where noise is not conspicuous. An object of the present invention is to provide an image processing program.

  In order to solve the above problems, the present invention employs the following means.

According to a first aspect of the present invention, an input image is divided into a plurality of areas, and a gradation conversion characteristic calculation unit that calculates a first gradation conversion characteristic for each area and the gradation conversion characteristic calculation unit A gradation conversion processing means for performing gradation conversion processing for each region using the first gradation conversion characteristics, and the first gradation conversion characteristics calculated by the gradation conversion characteristic calculation means; Noise reduction control characteristic calculating means for calculating a noise reduction control characteristic for adjusting the degree of noise reduction processing based on the characteristics of the image, and for the input image processed by the gradation conversion processing means, An image processing apparatus comprising: noise reduction processing means for performing noise reduction processing based on a noise reduction control characteristic.
Note that the region is a region including one or more pixels.

  According to such a configuration, the input image is divided into a plurality of areas, and gradation conversion characteristics are calculated for each area, and each area is based on the calculated gradation conversion characteristics and / or image characteristics. The degree of noise reduction processing is adjusted. This makes it possible to perform noise reduction processing that matches the characteristics of the image, rather than using the tone conversion characteristics as they are for noise reduction processing.

  According to a second aspect of the present invention, an input image is divided into a plurality of regions, a first gradation conversion characteristic is calculated for each region, and a first floor calculated by the first step is calculated. A second process of performing gradation conversion processing for each region using the tone conversion characteristics, and a noise reduction process based on the first gradation conversion characteristics and / or image characteristics calculated by the first process A third process of calculating a noise reduction control characteristic for adjusting the degree of noise, and a fourth process of performing noise reduction processing on the input image processed by the second process based on the noise reduction control characteristic And an image processing method.

  According to a third aspect of the present invention, an input image is divided into a plurality of regions, a first process for calculating a first gradation conversion characteristic for each region, and a first floor calculated by the first process. A second process for performing gradation conversion processing for each region using a tone conversion characteristic, and a noise reduction process based on the first gradation conversion characteristic and / or the image characteristic calculated by the first process A third process for calculating a noise reduction control characteristic for adjusting the degree of noise and a process for reducing noise on the input image processed by the second process based on the noise reduction control characteristic. An image processing program for causing a computer to execute processing.

  According to the present invention, it is possible to control the degree of noise reduction of an image that has undergone space variant tone conversion processing based on space variant tone conversion characteristics, image luminance information, and edge information. .

1 is a diagram illustrating a configuration example of an image processing apparatus according to a first embodiment of the present invention. It is the figure which showed notionally the noise reduction processing method which concerns on the 1st Embodiment of this invention. It is the figure which showed an example of the 1st information which concerns on the 1st Embodiment of this invention. It is the figure which showed an example of the 1st information which concerns on the 1st Embodiment of this invention. It is the figure which showed the structural example of the image processing apparatus which concerns on the 2nd Embodiment of this invention. It is the figure which showed notionally the noise reduction processing method which concerns on the 2nd Embodiment of this invention. It is the figure which showed an example of the 2nd information which concerns on the 2nd Embodiment of this invention. It is the figure which showed an example of the 2nd information which concerns on the 2nd Embodiment of this invention. It is the figure which showed the structural example of the image processing apparatus which concerns on the 3rd Embodiment of this invention. It is the figure which showed an example of the pixel area | region for calculating edge information. It is the figure which showed an example of the 3rd information which concerns on the 3rd Embodiment of this invention. It is the figure which showed an example of the 3rd information which concerns on the 3rd Embodiment of this invention. It is the figure which showed notionally the noise reduction processing method which concerns on the 3rd Embodiment of this invention. It is the figure which showed the structural example of the image processing apparatus which concerns on the 4th Embodiment of this invention. It is the figure which showed the operation | movement flow of the process concerning the 4th Embodiment of this invention. It is the figure which showed the operation | movement flow of the process concerning the 4th Embodiment of this invention. It is the figure which showed notionally the noise reduction processing method which concerns on the 4th Embodiment of this invention. It is the figure which showed notionally the conventional noise reduction processing method. It is the figure which showed the structural example of the conventional image processing apparatus.

  Embodiments of an image processing apparatus according to the present invention will be described below in detail with reference to the drawings.

[First Embodiment]
FIG. 1 is a block diagram showing a schematic configuration of an image processing apparatus according to the present embodiment.
In FIG. 1, the image processing apparatus of this embodiment is, for example, a digital camera, and includes an imaging unit 20 and an image processing apparatus 10.

The imaging unit 20, for example, photoelectrically converts an optical system 101 for forming a subject image and an optical subject image formed by the optical system 101 to obtain an electrical image signal (hereinafter, this image signal). And an imaging system 102 that outputs an “input image”).
The image processing apparatus 10 performs image processing including space variant gradation conversion processing on the input image acquired from the imaging system, and outputs the processed image.
The imaging unit 20 and the image processing apparatus 10 are connected.

  The image processing apparatus 10 includes an image processing unit 103, a gradation conversion characteristic calculation unit (tone conversion characteristic calculation unit) 104, a gradation conversion processing unit (tone conversion processing unit) 105, and a noise reduction control characteristic calculation unit (noise reduction). A control characteristic calculation unit) 106, a noise reduction processing unit (noise reduction processing unit) 107, and an image compression unit 108.

  The image processing unit 103 performs various image processing such as converting an analog input image signal acquired from the imaging system 102 into a digital signal, and outputs the input image signal after the various image processing to the gradation conversion characteristic calculation unit 104. .

  The gradation conversion characteristic calculation unit 104 divides the input image acquired from the image processing unit 103 into a plurality of areas, and calculates a first gradation conversion characteristic for each area. The gradation conversion characteristic calculation unit 104 outputs the calculated first gradation conversion characteristic to the gradation conversion processing unit 105 and the noise reduction control characteristic calculation unit 106.

  The gradation conversion processing unit 105 performs gradation conversion processing for each divided region using the first gradation conversion characteristic calculated by the gradation conversion characteristic calculation unit 104. Specifically, the gradation conversion processing unit 105 multiplies the input image with a space variant by multiplying the gradation conversion characteristic of each region calculated by the gradation conversion characteristic calculation unit 104 for each region of the input image. Tone gradation conversion is performed. The gradation conversion processing unit 105 outputs an image subjected to space variant gradation conversion to the noise reduction processing unit 107.

  For example, as shown in FIG. 2, when an input image 1 is input, tone conversion characteristics are calculated for each area, and gain distribution as shown in an image 2 that brightens the face area and background area of a person. Is calculated. If a space variant gradation conversion process is executed on the image 1 using this gradation conversion characteristic, an image that brightens the human face area and background area shown in the image 3 is obtained. At the same time, noise is also amplified in the face area and background area of the brightened person.

  The noise reduction control characteristic calculation unit 106 adjusts the degree of noise reduction based on the first gradation conversion characteristic and / or the image characteristic calculated by the gradation conversion characteristic calculation unit 104. Is calculated. Specifically, the noise reduction control characteristic calculation unit 106 has first information in which the first gradation conversion characteristic and the first gain are associated with each other, and the first gain corresponding to each region. Are respectively acquired from the first information, and the noise reduction control characteristic is calculated by multiplying the gradation conversion characteristic by the acquired first gain. The noise reduction control characteristic when the first gradation conversion characteristic is larger than the predetermined threshold may be larger than the noise reduction control characteristic when the first gradation conversion characteristic is smaller than the predetermined threshold.

  FIG. 3 shows an example of the first information. In FIG. 3, the horizontal axis indicates the gradation conversion characteristics, and the vertical axis indicates the first gain. As shown in FIG. 3, the first gain when the first gradation conversion characteristic is greater than or equal to the predetermined threshold Th1 is greater than the first gain when the first gradation conversion characteristic is smaller than the predetermined threshold Th1. Is also set to a large value. In this example, when the threshold Th1 is set to 1.5, the first gain given when the gradation conversion characteristic exceeds the threshold 1.5 is 2, and the gradation conversion characteristic does not exceed the threshold 1.5 The first gain is 1. More specifically, the noise reduction control characteristic is the same as the gradation conversion characteristic in a range where the gradation conversion characteristic does not exceed the threshold Th1, and in the range where the threshold Th1 exceeds 1.5, the noise reduction control characteristic is the same. The characteristic is twice the tone conversion characteristic.

  Next, the above contents will be described with reference to the drawings. In the image 2 of FIG. 2, a case where regions having gradation conversion characteristics equal to or higher than a predetermined threshold are a human face region and a background region will be described. The noise reduction control characteristic calculation unit 106 sets a first gain that greatly reduces noise in the human face area and the background area (the gain distribution at that time is as shown in image 4). Parts other than the face area and background area are given the same gain.

  The noise reduction control characteristic calculation unit 106 outputs the calculated noise reduction control characteristic to the noise reduction processing unit 107.

  The noise reduction processing unit 107 performs a process of reducing noise on the input image processed by the gradation conversion processing unit 105 based on the noise reduction control characteristics. The image subjected to noise reduction processing by the noise reduction processing unit 107 is input to the image compression unit 108. The image compression unit 108 compresses the image signal supplied from the noise reduction processing unit 107 into, for example, a JPEG format and stores the image signal in a recording medium 109 such as a memory card.

Next, the operation of the image processing apparatus according to this embodiment will be described.
First, a subject image formed by the optical system 101 is converted from an optical subject to an electrical signal by the imaging system 102 and output. The input image output from the imaging system 102 is supplied to the image processing unit 103. The image processing unit 103 performs various types of image processing, and the input image is supplied to the gradation conversion characteristic calculation unit 104. A gradation conversion characteristic calculation unit 104 calculates gradation conversion characteristics corresponding to each area of the input image. The tone conversion processing unit 105 performs space variant tone conversion processing on the input image signal based on the calculated tone conversion characteristics.

  Subsequently, the noise reduction control characteristic calculation unit 106 calculates the noise reduction control characteristic using the space variant gradation conversion characteristic calculated by the gradation conversion characteristic calculation unit 104. The noise reduction processing unit 107 performs noise reduction on the tone-converted input image signal based on noise reduction control characteristics. In this way, the image signal of the input image that has been subjected to the gradation conversion processing for each region is supplied to the image compression unit 108 and compressed based on a predetermined format, and is stored in the recording medium 109 such as a memory card. To be recorded.

  As described above, according to the image processing apparatus of the present embodiment, the space variant tone conversion processing is performed on the input image, and the degree of noise reduction processing based on the space variant tone conversion characteristics. Adjust. In this case, the gain when the gradation conversion characteristic is equal to or greater than the predetermined threshold is set to a larger value than the gain when the gradation conversion characteristic is smaller than the predetermined threshold. Noise can be greatly reduced in areas where noise is greatly amplified, and noise reduction is applied to areas where space variant tone conversion characteristics are small and noise amplification is small, and where noise is inconspicuous. Thus, the resolution of the input image can be maintained.

In the above-described embodiment, processing by hardware is assumed as the image processing apparatus, but it is not necessary to be limited to such a configuration. For example, a configuration in which software is separately processed based on output signals from each sensor is also possible. In this case, the image processing apparatus includes a main storage device such as a CPU and a RAM, and a computer-readable recording medium on which a program for realizing all or part of the above processing is recorded. Then, the CPU reads out the program recorded in the storage medium and executes information processing / calculation processing, thereby realizing processing similar to that of the above-described image processing apparatus.
Here, the computer-readable recording medium means a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Alternatively, the computer program may be distributed to the computer via a communication line, and the computer that has received the distribution may execute the program.

  Although the simplest noise reduction characteristic calculation method is shown in the first embodiment, the present invention is not limited to this method. For example, in the noise reduction characteristic calculation method shown in the first embodiment, the characteristic changes abruptly before and after the threshold, and an artifact that becomes signal distortion may occur in that region. For this reason, in order to reduce the artifact, a large gain may be given gradually before and after the threshold as shown in FIG.

[Second Embodiment]
Next, an image processing apparatus according to a second embodiment of the present invention will be described with reference to the drawings.
The image processing apparatus according to this embodiment is different from the first embodiment in that the luminance information of the image is taken into account when the noise reduction control characteristic calculation unit calculates the noise reduction control characteristic. Hereinafter, regarding the image processing apparatus according to the present embodiment, description of points that are common to the first embodiment will be omitted, and differences will be mainly described.

  FIG. 5 is a block diagram showing a configuration example of an image processing apparatus according to the second embodiment of the present invention. As shown in FIG. 5, the image processing apparatus according to the present embodiment includes a noise reduction control characteristic calculation unit 126 instead of the noise reduction control characteristic calculation unit 106 (see FIG. 1) according to the first embodiment described above. In addition, a luminance information calculation unit 140 is added.

  The luminance information calculation unit 140 calculates average luminance for each region divided by the gradation conversion characteristic calculation unit 104, and outputs information on the calculated average luminance for each region to the noise reduction control characteristic calculation unit 126.

  The noise reduction control characteristic calculation unit 126 calculates the noise reduction control characteristic based on the average luminance for each region calculated by the luminance information calculation unit 140. Specifically, the noise reduction control characteristic calculation unit 126 has second information in which the average luminance of the image is associated with the second gain, and the second gain corresponding to the average luminance of the region is obtained. The noise reduction control characteristic is calculated by obtaining from the second information and multiplying the gradation conversion characteristic by the obtained second gain. Further, the noise reduction control characteristic in the region where the luminance of the image is lower than the predetermined threshold may be larger than the noise reduction control characteristic in the region where the luminance of the image is higher than the predetermined threshold.

  FIG. 7 shows an example of the second information. In FIG. 7, the horizontal axis indicates the luminance information of the image, and the vertical axis indicates the second gain given to the gradation conversion characteristics. As shown in FIG. 7, the second gain when the average luminance is equal to or lower than the predetermined threshold Th2 may be set to a value larger than the second gain when the average luminance is higher than the predetermined threshold Th2. In the present embodiment, the second gain is doubled when the luminance information of each area is equal to or less than the threshold Th2, and the second gain is multiplied when the luminance information exceeds the threshold Th2.

  More specifically, when the average luminance is low luminance that does not exceed the threshold value Th2, the value obtained by doubling the entire gradation conversion characteristic is used as the noise reduction control characteristic, so that the average luminance of the image exceeds the predetermined threshold value. In the dark range, the noise reduction processing is greatly performed. On the other hand, in a bright range where the threshold value Th2 of the average luminance of the image is higher, the noise reduction process is executed with the value of the gradation conversion characteristic as it is as the noise reduction control characteristic.

  More specifically, if the luminance of the image is a low luminance area smaller than a predetermined threshold in the human face area and the human torso area of the image 2 in FIG. 6, noise reduction is performed for this area. Is calculated (image 4 shows a conceptual diagram of a gain distribution in which a gain is set high in a low luminance region). In this way, the noise reduction processing characteristics are adjusted using the calculated noise reduction control characteristics, so that the noise in the human face area and the human torso area is greatly reduced, and other areas (in the vicinity of the light source) The resolution of the area and the background area) is maintained.

  As described above, according to the image processing apparatus according to the present embodiment, in an image subjected to space variant tone conversion characteristics, the degree of noise reduction processing is adjusted using the luminance information of the image, and the image Increase noise reduction control characteristics in low luminance areas. As a result, it is possible to greatly reduce noise only in a low-luminance region of an image where noise is conspicuous, and to maintain the resolution of other regions.

  Note that the second information in which the luminance information and the second gain for calculating the noise reduction control characteristics in the present embodiment are associated with each other indicates the simplest method, but is not limited thereto. For example, in FIG. 7, since the characteristics change abruptly before and after the threshold value, an artifact may occur in that region. For this reason, in order to reduce the artifact, the gain may be gradually reduced around the threshold as shown in FIG.

[Third Embodiment]
Next, an image processing apparatus according to a third embodiment of the present invention will be described with reference to the drawings.
The image processing apparatus according to this embodiment is different from the first and second embodiments in that image edge information is considered when the noise reduction control characteristic calculation unit calculates the noise reduction control characteristic. Hereinafter, regarding the image processing apparatus according to the present embodiment, description of points that are the same as those in the first and second embodiments will be omitted, and different points will be mainly described.

  FIG. 9 is a block diagram showing a configuration example of an image processing apparatus according to the third embodiment of the present invention. As shown in FIG. 9, in the image processing apparatus according to the present embodiment, a noise reduction control characteristic calculation unit 136 is used instead of the noise reduction control characteristic calculation unit 106 (see FIG. 1) according to the first embodiment described above. In addition, an edge information calculation unit 141 is added.

  The edge information calculation unit 141 calculates edge information for each predetermined region divided by the gradation conversion characteristic calculation unit 104, and is an edge region or a non-edge region (non-edge region) according to the obtained edge information. This determination result is output to the noise reduction control characteristic calculation unit 136.

As shown in FIG. 10, the edge information calculation unit 141 calculates edge information from a 3 × 3 area surrounding p22, where p22 is a predetermined area to be processed. Dh, Dv, Dz, and Dn are edge amounts in the horizontal direction, vertical direction, right-upward diagonal direction, and right-down diagonal direction, respectively, and the largest value is calculated as edge information of p22. The edge amounts Dh, Dv, Dz, Dn are expressed by the following formulas. Here, p21, p23, p12, p32, p13, p31, p11, and p33 are 3 × 3 peripheral regions surrounding p22.
Dh = | p21−p22 | + | p23−p22 |
Dv = | p12−p22 | + | p32−p22 |
Dz = | p13−p22 | + | p31−p22 |
Dn = | p11−p22 | + | p33−p22 |

  The noise reduction control characteristic calculation unit 136 calculates the noise reduction control characteristic based on the edge information calculated by the edge information calculation unit 141. Specifically, the calculated edge information of p22 is compared with a predetermined threshold value Th3, and if it is equal to or greater than the predetermined threshold value Th3, it indicates that the difference between the processing target region p22 and the adjacent region is large, and the processing target region It is determined that p22 belongs to the edge region. On the other hand, when the edge information of p22 is smaller than the predetermined threshold Th3, it indicates that the difference between the processing target region p22 and the adjacent region is small, and it is determined that the processing target region p22 belongs to the non-edge region. The noise reduction control characteristic of the non-edge region is preferably larger than the noise reduction control characteristic of the edge region.

  More specifically, the noise reduction control characteristic calculation unit 136 has third information in which edge information and a third gain are associated with each other, and the third gain corresponding to the edge information is stored in the third gain. The noise reduction control characteristic is calculated by acquiring the information from the information and multiplying the gradation conversion characteristic by the acquired third gain.

  The edge information of an image is an index indicating whether or not each divided area belongs to an edge area.

  FIG. 11 shows an example of the third information. In FIG. 11, the horizontal axis represents image edge information, and the vertical axis represents a third gain given to the gradation conversion characteristics. The third gain when the edge information of the image is a non-edge region (region below the threshold Th3) is larger than the third gain when the edge information of the image is an edge region (region larger than the threshold Th3). Set it to a value.

  When the edge information of the area to be processed is equal to or less than the threshold Th3, the area to be processed is a non-edge area, and therefore the gradation conversion characteristic of the area is doubled as the noise reduction control characteristic. . On the other hand, when the edge information of the region to be processed exceeds a predetermined threshold Th3, it is determined that the region is an edge region, and the tone conversion characteristic of the region is directly used as the noise reduction control characteristic. In other words, the area is not an edge area, but an area where noise is conspicuous is greatly reduced.

  FIG. 13 is a diagram conceptually illustrating the noise reduction processing method according to the third embodiment. In FIG. 13, the edge information of a person's face area and background area is a non-edge area, and the noise reduction control characteristic is calculated so that the value of the area becomes large. Since the input image has been subjected to noise reduction processing using this noise reduction control characteristic, noise in the human face area and background area is greatly reduced, and other areas (the area around the light source and the human torso area) The sense of resolution is maintained.

  As described above, according to the image processing apparatus according to the present embodiment, in an image subjected to space variant tone characteristics, the degree of noise reduction processing is adjusted using the edge information of the image, and the non-image is displayed. Increase noise reduction control characteristics in the edge region. As a result, it is possible to greatly reduce noise only in a region where noise is conspicuous in the input image and to maintain the sense of resolution in other regions.

  Note that the third information in which the edge information and the third gain for calculating the noise reduction control characteristic in the present embodiment are associated with each other indicates the simplest method, but is not limited thereto. For example, in FIG. 11, since the characteristics change abruptly before and after the threshold value, there is a possibility that artifacts will occur in that region. For this reason, in order to reduce the artifact, the gain may be gradually reduced before and after the threshold as shown in FIG.

[Fourth Embodiment]
Next, an image processing apparatus according to a fourth embodiment of the present invention will be described with reference to the drawings.
The image processing apparatus according to this embodiment is different from the first, second, and third embodiments in that the noise reduction control characteristic calculation unit calculates a noise reduction control characteristic. Hereinafter, the image processing apparatus according to the present embodiment will not be described with respect to the points common to the first, second, and third embodiments, and different points will be mainly described.

  FIG. 14 is a block diagram showing a configuration example of an image processing apparatus according to the fourth embodiment of the present invention. As shown in FIG. 14, the image processing apparatus according to the present embodiment includes a luminance information calculation unit 140 and an edge information calculation unit 141, and the noise reduction control characteristic calculation unit 106 (see FIG. 14) according to the first embodiment described above. 1), a noise reduction control characteristic calculation unit 146 is provided.

A method of calculating the noise reduction control characteristic by the noise reduction control characteristic calculation unit 146 will be described with reference to FIGS. 15 and 16.
Space variant tone conversion characteristics, image luminance information, and image edge information are input (step SA1 in FIG. 15). Subsequently, the space variant tone conversion characteristics of the region to be processed are compared with a predetermined threshold Th1 (step SA2 in FIG. 15). As a result of comparison, when Th1 is exceeded, the gain is doubled (step SA3-2 in FIG. 16), and when Th1 is not exceeded, the gain is doubled (step SA3- in FIG. 15). 1). The gain given in step SA3-1 and step SA3-2 is defined as gain A.

  Regardless of whether the processing proceeds to either step SA3-1 or step SA3-2, the luminance information of the image is subsequently calculated, and it is determined whether the luminance information exceeds a predetermined threshold Th2 (FIG. 15 step SA4-1, step SA4-2 in FIG. When the luminance information does not exceed the threshold Th2, twice the gain A calculated in the previous stage is calculated as the gain B (step SA5-1 in FIG. 15, step SA5-3 in FIG. 16), and the luminance information is When the threshold Th2 is exceeded, the value of the gain A is directly used as the gain B (step SA5-2 in FIG. 15 to step SA5-4 in FIG. 16).

  Even when the process proceeds from step SA6-1 to any one of steps SA6-4, the edge information of the image is subsequently calculated, and it is determined whether the edge information exceeds a predetermined threshold Th3 ( Step SA7-1 in FIG. 15 to Step SA7-8 in FIG. 16). When the edge information is equal to or less than the threshold Th3, the predetermined area is determined as a non-edge area, and twice the gain B calculated in the previous stage is calculated as the gain C. On the other hand, when the edge information exceeds the threshold Th3, the predetermined area is determined as the edge area, and the value of the gain B is directly calculated as the gain C.

  The noise reduction control characteristic is calculated by multiplying the gradation conversion characteristic of the region to be processed by the gain C calculated as described above (step SA8 in FIG. 15), and this process is terminated.

  FIG. 17 is a diagram conceptually illustrating a noise reduction processing method according to the fourth embodiment. In FIG. 17, the space variant tone conversion characteristics of the human face area and the background area are larger than a predetermined threshold Th1. In addition, the human face area and the human torso area indicate low-luminance areas where the luminance information of the image is smaller than an arbitrary threshold value Th2, and the non-edge areas where the human face area and the background area are smaller than a predetermined threshold value Th3. Yes.

  Here, the area where the space-variant tone conversion characteristic is a value larger than the predetermined threshold Th1, the luminance is low, and the area is a non-edge area is a human face area. In the present embodiment, the noise reduction control characteristic is calculated such that the value is larger in the area that is larger than the space variant gradation conversion characteristic, low brightness, and non-edge area, and thus this noise reduction control. When the noise reduction process is executed using the characteristics, the noise in the human face area is greatly reduced. On the other hand, it shows that the sense of resolution of the area around the light source, the area of the human torso, and other areas as the background area is maintained.

  As described above, the image processing apparatus according to the present embodiment uses the image characteristics and / or the space variant tone conversion characteristics, the image luminance information, and the edge information, and obtains the final information acquired by each information. A specific gain is obtained, and noise reduction processing is performed using this final gain. In the present embodiment, when the space variant tone characteristics are larger than a predetermined threshold, and the space variant tone characteristics are set so that the noise reduction control value is increased in an area where the luminance of the image is low and a non-edge area. Adjust the degree of noise reduction processing. As a result, compared to the first, second, and third embodiments, it is possible to narrow down a region where noise is conspicuous, greatly reduce noise for the region, and other regions where noise is not conspicuous are: It becomes possible to maintain a sense of resolution.

  Specifically, in the first embodiment, noise is greatly increased by space-variant gradation conversion, but a region where the luminance of the image is high and noise is not noticeable (for example, the background region in FIG. 2) is greatly increased. In order to reduce noise, the resolution of the area deteriorates. Similarly, in the second embodiment, an area where the luminance of the image is low is an area where noise is conspicuous, but an area where noise is not greatly increased by space variant gradation conversion, in other words, noise reduction is performed. Since an area that does not need to be significantly reduced (for example, the area of the human torso in FIG. 6) is significantly reduced in noise, the resolution of the area deteriorates.

  On the other hand, in the fourth embodiment, a space variant tone characteristic is larger than an arbitrary threshold and the image brightness is low, and a non-edge region, that is, a region where noise is conspicuous (for example, the person in FIG. 17). It is possible to significantly reduce noise only in the face area) and maintain the resolution of the other areas, so that it is possible to perform noise reduction processing according to the characteristics of the image.

  The image processing apparatuses according to the first, second, and third embodiments may be mounted on products such as a stationary camera for broadcasting, an ENG camera, a consumer handy camera, and a digital camera. Furthermore, the present invention may be used for an image signal correction program (CG program) that handles moving images, an image editing apparatus, and the like.

  In the image processing apparatus according to the present embodiment, the noise reduction control characteristic calculation unit 146 obtains a gain from the three types of information of the gradation conversion characteristic, the image luminance information, and the edge information, and calculates the obtained gain as a scale. Although the key conversion characteristic is multiplied, the present invention is not limited to this. For example, the noise reduction control characteristic calculation unit 146 has first information in which the gradation conversion characteristic and the first gain are associated with each other, and acquires the first gain corresponding to each region from the first information. A first gain acquisition unit (not shown) that stores the second information in which the average luminance and the second gain are associated with each other, and acquires the second gain corresponding to the average luminance from the second information. A second gain acquisition unit (not shown) has third information in which edge information and third gain are associated with each other, and acquires a third gain corresponding to the edge information from the third information. At least any two of the third gain acquisition units (not shown) are provided, a final gain is obtained using the gain determined by each acquisition unit, and this final gain is used as a gradation conversion characteristic. Multiplying noise reduction control characteristics by multiplication It is also possible to output.

104 gradation conversion characteristic calculation unit 105 gradation conversion processing units 106, 126, 136, 146 noise reduction control characteristic calculation unit 107 noise reduction processing unit 140 luminance information calculation unit 141 edge information calculation unit

Claims (10)

A gradation conversion characteristic calculating means for dividing the input image into a plurality of areas and calculating a first gradation conversion characteristic for each of the areas;
Gradation conversion processing means for performing gradation conversion processing for each of the areas using the first gradation conversion characteristics calculated by the gradation conversion characteristic calculation means;
Noise reduction control characteristic calculation for calculating a noise reduction control characteristic for adjusting the degree of noise reduction processing based on the first gradation conversion characteristic and / or image characteristic calculated by the gradation conversion characteristic calculation unit Means,
Noise reduction processing means for performing processing for reducing noise based on the noise reduction control characteristics for the input image processed by the gradation conversion processing means;
An image processing apparatus comprising:   The noise reduction control characteristic when the first gradation conversion characteristic is larger than a predetermined threshold is made larger than the noise reduction control characteristic when the first gradation conversion characteristic is smaller than the predetermined threshold. The image processing apparatus according to claim 1. The noise reduction control characteristic calculation unit has first information in which the first gradation conversion characteristic and the first gain are associated with each other, and the first gain corresponding to the region is the first gain. Obtaining a noise reduction control characteristic by multiplying the gradation conversion characteristic by the acquired first gain, and obtaining from the information;
The first gain when the first gradation conversion characteristic is equal to or greater than a predetermined threshold is set to a value larger than the first gain when the first gradation conversion characteristic is smaller than the predetermined threshold. The image processing apparatus according to claim 2.   4. The noise reduction control characteristic in a region where the luminance of the image is lower than a predetermined threshold is made larger than the noise reduction control characteristic in a region where the luminance of the image is higher than the predetermined threshold. An image processing apparatus according to claim 1. The noise reduction control characteristic calculation unit has second information in which the average luminance of the image is associated with the second gain, and the second gain corresponding to the average luminance of the region is the second information. And calculating the noise reduction control characteristic by multiplying the gradation conversion characteristic by the acquired second gain.
5. The second gain when the average luminance is equal to or lower than a predetermined threshold is set to a value larger than the second gain when the average luminance is higher than the predetermined threshold. The image processing apparatus described. The region to be processed of the image includes edge information calculation means for calculating edge information,
6. The image processing apparatus according to claim 1, wherein the noise reduction control characteristic of the non-edge area is made larger than the noise reduction control characteristic of the edge area. The noise reduction control characteristic calculation unit has third information in which the edge information and a third gain are associated with each other, and a third gain corresponding to the edge information of the region is obtained from the third information. Obtaining a noise reduction control characteristic by multiplying the gradation conversion characteristic by the acquired third gain,
The third gain when the edge information of the image is a non-edge region is set to a larger value than the third gain when the edge information of the image is an edge region. Item 7. The image processing apparatus according to Item 6. The noise reduction control characteristic calculation means is:
First gain acquisition means for storing the first information in which the gradation conversion characteristic and the first gain are associated with each other, and acquiring the first gain corresponding to the region from the first information;
Second gain acquisition means for holding second information in which the average luminance and the second gain are associated, and acquiring a second gain corresponding to the average luminance from the second information;
3rd gain acquisition means which holds the 3rd information where edge information and the 3rd gain were matched, and acquires the 3rd gain corresponding to the edge information from the 3rd information at least. A noise reduction control characteristic is calculated by obtaining a final gain using the gain determined by each of the two means, and multiplying the gradation conversion characteristic by the final gain. The image processing apparatus according to claim 1. A first step of dividing the input image into a plurality of regions and calculating a first gradation conversion characteristic for each region;
A second step of performing gradation conversion processing for each region using the first gradation conversion characteristic calculated in the first step;
A third step of calculating a noise reduction control characteristic for adjusting a degree of noise reduction processing based on the first gradation conversion characteristic and / or the image characteristic calculated in the first step;
A fourth step of performing noise reduction processing on the input image processed in the second step based on the noise reduction control characteristics;
An image processing method comprising: A first process for dividing the input image into a plurality of regions and calculating a first gradation conversion characteristic for each region;
A second process for performing a gradation conversion process for each region using the first gradation conversion characteristic calculated by the first process;
A third process for calculating a noise reduction control characteristic for adjusting the degree of the noise reduction process based on the first gradation conversion characteristic and / or the image characteristic calculated by the first process;
A fourth process for performing a process of reducing noise based on the noise reduction control characteristic for the input image processed by the second process;
An image processing program for causing a computer to execute.

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