JP6858073B2 - Image processing device, image processing method, and program - Google Patents

Description

The present invention relates to an image processing apparatus, an image processing method, and a program.

In recent years, there has been a tendency to miniaturize the pixels of the image sensor, and the noise of the image signal obtained from the image sensor tends to increase due to the miniaturization of the pixels. Therefore, as a method of suppressing this noise by signal processing, a method using multi-rate signal processing is known. For example, there is a method of dividing an image signal into a plurality of frequency components, suppressing noise in each divided image, and then resynthesizing the image signal (see Patent Document 1). In Patent Document 1, an image signal is divided into images having a plurality of frequency components, and noise suppression (NR) processing is performed on each divided image. There are various methods for dividing the frequency component. For example, a low-frequency image can be generated by pre-filtering the original image and then thinning the size in half. Further, the high-frequency image can be generated by enlarging the low-frequency image to the same size as the original image and obtaining the difference between the original image and the enlarged image. By dividing the image into a plurality of frequency components in this way, it becomes possible to apply noise suppression processing suitable for the frequency components to each divided image. Further, by reducing the image size, it is possible to reduce noise with a small filter length.

When noise suppression is performed, high-frequency noise is visually inconspicuous due to the fine graininess of the noise, while low-frequency noise is visually conspicuous due to the large granularity, and is lower than high-frequency noise. It is desirable to strongly remove the noise. In addition, the composition processing of the divided image can be executed by a simple operation such as enlarging the low frequency image and adding it to the high frequency image. However, if the divided image is blurred by the noise suppression processing, after the composition processing. In the image of, the blur of the corresponding frequency band remains as it is. Therefore, in the method of suppressing noise by dividing it into frequency components, it is necessary to suppress the noise suppression effect to an extent that blur can be tolerated in each frequency band while performing different noise suppression for each frequency component.

As another noise suppression method, first, a plurality of reduced images are generated from an image signal, noise suppression processing is performed on the plurality of reduced images, and an edge signal is extracted to determine the composition ratio of each image based on the edge signal. There is a method of calculating and synthesizing a plurality of image signals based on the synthesizing ratio (see Patent Document 2). In this method, a reduced image in which the horizontal and vertical sizes are halved and a reduced image in which the sizes are halved are generated. Then, noise suppression processing is performed on each image, and an edge signal is extracted from the reduced image. In image composition, the edge signal is enlarged to the original size, the composition ratio is determined based on the enlarged edge signal, the strong part of the edge signal uses a larger size image, and the weak part of the edge signal is reduced. Use an enlarged image of the original size.

As a result, the original size image is often used for the edge portion of the combined image, and conversely, the reduced image is not often used. Therefore, even if the noise suppression process is applied to the reduced image and the edge portion is blurred, the final image is not affected. Therefore, it is possible to apply a strong noise suppression process to the reduced image, and it is possible to obtain an image after composition in which the noise suppression effect of the low frequency component is enhanced without blurring the edges.

Japanese Unexamined Patent Publication No. 2008-15741 Japanese Unexamined Patent Publication No. 2009-199104

However, in the method of calculating the composition ratio described in Patent Document 2, since the edge signal detected from the reduced image is enlarged, the edge signal becomes thicker than the actual edge. As a result, a range wider than the actual edge range in the original size image is detected as an edge. Then, since the compositing process is performed with this fat edge signal, the image of the upper layer is used even around the edge, and there is a possibility that noise remains around the edge.

Therefore, the present invention provides a technique that makes it possible to enhance the noise suppression effect around the edge in the noise suppression processing.

In order to achieve the above object, the present invention is an image processing apparatus.
A reduction means that reduces the input image and generates a reduced image,
A first detection means that performs edge detection on the input image and generates a first edge signal,
A second detection means that performs edge detection on the reduced image and generates a second edge signal,
A first noise suppression means for generating a first noise suppression image by performing noise suppression processing on the input image,
A second noise suppression means that performs noise suppression processing on the reduced image to generate a second noise suppression image,
A correction means that corrects the second edge signal and outputs the corrected edge signal.
An enlarging means for enlarging the corrected edge signal and the second noise-suppressed image and outputting the enlarged edge signal and the enlarged noise-suppressed image.
A calculation means that adds the enlarged edge signal and the first edge signal and calculates the composition ratio based on the value of the added edge signal.
A compositing means for compositing the first noise-suppressed image and the enlarged noise-suppressed image at the compositing ratio, and
With
When the value of the second edge signal exceeds a predetermined value, the correction means corrects the value of the second edge signal so that the value of the second edge signal does not exceed the predetermined value. ,
In the calculation means, the smaller the value of the edge signal after the addition, the higher the composition ratio of the enlarged noise suppression image, and the larger the value of the edge signal after the addition, the higher the first noise suppression image. Increase the synthesis ratio of.

According to the present invention, it is possible to provide a technique for enhancing the noise suppression effect around the edge in the noise suppression processing.

The block diagram which shows the structural example of the image processing apparatus corresponding to the embodiment of an invention. The block diagram which shows the structural example of the noise suppression processing part for each band corresponding to the Embodiment of this invention. The flowchart which shows an example of the processing in the image processing apparatus corresponding to the embodiment of the invention. The figure for demonstrating the noise suppression processing corresponding to the embodiment of the invention, the figure for demonstrating the correction process of the 2nd edge signal, and the figure for demonstrating the calculation process of a synthesis ratio.

Hereinafter, embodiments for carrying out the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a configuration example of an image processing device 100 corresponding to an embodiment of the present invention. In the present embodiment, a digital camera will be described as an example of the image processing device 100, but as long as it is a device capable of performing noise suppression processing on an image signal, it is not limited to a digital camera, but a digital video camera, a personal computer, or a mobile phone. It can also be realized as an arbitrary information processing device such as a telephone, a smartphone, a PDA, a tablet terminal, a portable media player, or an image pickup device. Further, FIG. 1 shows a configuration including an optical system 101 to an A / D converter 104 in consideration of a case where it functions as a digital camera or the like. However, the image processing device 100 may be realized in a form that does not have the configuration from the optical system 101 to the A / D converter 104. Further, in the image processing device 100 of FIG. 1, each block may be configured in hardware using a dedicated logic circuit or memory, except for specific physical devices such as an image sensor and a display element. Alternatively, it may be configured in software by executing a processing program stored in the memory by a computer such as a CPU.

In FIG. 1, the optical system 101 includes a lens group composed of a zoom lens and a focus lens, an aperture device, and a shutter device. The optical system 101 adjusts the magnification, focus position, or amount of light of the subject image reaching the image sensor 102. The image sensor 102 is a photoelectric conversion element such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor) image sensor, and converts a subject image into an electric signal to generate an image signal. The preprocessing circuit 103 includes a CDS (Correllated Double Sampling) circuit and an amplifier circuit. The CDS circuit suppresses the dark current contained in the image signal generated by the image sensor 102, and the amplifier circuit amplifies the image signal output from the CDS circuit. The A / D converter 104 converts the image signal output from the preprocessing circuit 103 into a digital image signal, and outputs the image signal to the image processing unit 105.

The image processing unit 105 executes predetermined image processing including white balance processing, noise reduction (NR: Noise Reduction) processing, gradation conversion processing, edge enhancement correction processing, and the like on the input image signal, and processes the input image signal. The resulting image signal is output as a luminance signal Y and color difference signals U and V. In addition, the image processing unit 105 can also calculate the brightness value of the subject and the focusing value indicating the focus state of the subject from the image signal. The image processing unit 105 can perform the same image processing not only on the image signal output from the A / D converter 104 but also on the image signal read from the recording medium 109.

The control unit 106 controls the operation in each block constituting the digital camera 100 corresponding to the present embodiment, and controls the operation of the digital camera 100. The drive control of the optical system 101 and the image sensor 102 is also performed based on the brightness value obtained from the image signal processed by the image processing unit 105 and the instruction input from the operation member 110. The display memory 107 is a memory that temporarily stores an image signal that is a source of an image to be displayed on the display device 108. The display device 108 is composed of a liquid crystal display or an organic EL (Electro Luminescence) display, and displays an image using an image signal generated by the image sensor 102 or an image signal read from the recording medium 109. The display device 108 can also function as an electronic viewfinder by updating and displaying a continuous image signal read from the image sensor 102 at any time. Further, the display device 108 shows the status display of the digital camera 100, character information such as shutter speed, aperture value, and sensitivity information determined by the user side or the digital camera 100 side, and the brightness distribution measured by the image processing unit 105. It is also possible to display a graph or the like.

The recording medium 109 may be detachably configured to be attached to or detached from the digital camera 100, or may be built into the digital camera 100. The operation member 110 is a member that the user operates to input a predetermined instruction to the digital camera 100, and can be composed of various buttons, switches, dials, touch panels, and the like. The bus 111 is used for exchanging image signals between the image processing unit 105, the control unit 106, the display memory 107, and the recording medium 109.

Next, an example of the operation of the digital camera 100 at the time of shooting in the present embodiment will be described. When the operation member 110 is operated by the user and an instruction to start shooting preparation is input, the control unit 106 starts controlling the operation of each block.

First, the image sensor 102 photoelectrically converts the subject image transmitted through the optical system 101 to generate an analog image signal, and the A / D converter 104 digitally images the analog image signal processed by the preprocessing circuit 103. Convert to a signal. The image processing unit 105 performs image processing such as white balance processing, noise suppression processing, gradation conversion processing, and contour correction processing on the image signal output from the A / D converter 104. The image signal processed by the image processing unit 105 is temporarily held in the display memory 107, and the image signal read from the display memory 107 is displayed as an image on the display device 108. As described above, the display device 108 functions as an electronic viewfinder by updating the subject image in real time and displaying it on the display device 108 based on the image signal continuously generated by the image sensor 102.

Then, these processes are repeated until the user operates the shutter button included in the operation member 110. When the user operates the shutter button, the control unit 106 re-adjusts the operation of the optical system 101 based on the brightness value and the in-focus value obtained by the image processing unit 105 to shoot a still image. The image processing unit 105 performs various image processing including noise suppression processing on the image signal of the captured still image, and the recording medium 109 contains a still image file based on the image signal output from the image processing unit 105. Recorded.

Next, the noise suppression process in the image processing unit 105 will be described in detail. FIG. 2 is a block diagram showing a detailed configuration example of the band-specific noise suppression processing unit 200 included in the image processing unit 105. The band-specific noise suppression processing unit 200 of the present embodiment includes a reduction processing unit 201, a noise suppression processing unit 202, an edge signal detection processing unit 203, a noise suppression processing unit 204, an edge signal detection processing unit 205, and an edge signal correction processing unit 206. , Enlargement processing unit 207, enlargement processing unit 208, composition ratio calculation processing unit 209, and image composition processing unit 210.

In FIG. 2, the input image input to the band-specific noise suppression processing unit 200 is input in parallel to the reduction processing unit 201, the noise suppression processing unit 202, and the edge signal detection processing unit 203, and is processed respectively. The band-specific noise suppression processing unit 200 has two noise suppression processing units, a noise suppression processing unit 202 and a noise suppression processing unit 204, but the noise suppression processing unit 202 is an input of the original size that has not been reduced. It is a processing unit that suppresses noise on an image, and the noise suppression processing unit 204 is a processing unit that suppresses noise on an image reduced by the reduction processing unit 201. Similarly, the band-specific noise suppression processing unit 200 has two edge detection processing units, an edge signal detection processing unit 203 and an edge signal detection processing unit 205, but the edge signal detection processing unit 203 is reduced. It is a processing unit that performs edge detection on an input image of the original size that has not been used, and the edge signal detection processing unit 205 is a processing unit that performs edge detection on an image reduced by the reduction processing unit 201. The image resulting from the noise suppression processing and the edge signal generated by the edge detection are combined through the correction processing, the enlargement processing, and the composition ratio calculation processing corresponding to the present embodiment to obtain an output image.

Hereinafter, the processing in the band-specific noise suppression processing unit 200 corresponding to the present embodiment will be described in more detail with reference to the flowchart of FIG. FIG. 3 is a flowchart showing an example of a processing procedure by the band-specific noise suppression processing unit 200. The processing corresponding to the flowchart can be realized, for example, by executing a program (stored in ROM or the like) corresponding to one or more processors functioning as the image processing unit 105 and the band-specific noise suppression processing unit 200. When the image processing unit 105 receives the image signal output from the A / D converter 104, the pixel color interpolation processing is performed, and then the band-specific noise suppression processing unit 200 performs each color (for example, R (red)). ), G (green), and B (blue) are subjected to the processing shown in FIG. The white balance processing, color conversion processing, gradation conversion processing, etc. are omitted.

First, in S301, the reduction processing unit 201 applies a pre-filter to the input image and then generates a reduced image in which pixels are thinned out to 1/2 size in the horizontal and vertical directions, respectively. As a pre-filter, a coefficient of [1 2 1] is applied both horizontally and vertically. The coefficient is a coefficient for averaging (smoothing) the weighting of the pixel of interest and the weighting of each pixel adjacent to both sides of the pixel of interest at a ratio of 2: 1. As a result, the reduced image is generated as an image composed of low frequency components in the input image.

Next, in S302, the noise suppression processing unit 202 performs noise suppression processing on the same input image as the input image processed by the reduction processing unit 201 in S301. The noise-suppressed image generated at this time is hereinafter referred to as the first NR image. In the noise suppression process, for example, a reference area of 7 × 7 pixels is set around the pixel of interest as shown in FIG. 4A, and each pixel of the reference area is different from the pixel of interest. Then, the average value is calculated only for the pixels whose difference is within the threshold value, and the average value is output as the value of the pixel of interest. By performing the noise suppression processing for each pixel, it is possible to obtain an output image in which noise is suppressed for the entire input image to be processed. The threshold value may be changed for each image, and further, the threshold value may be changed according to the signal level in consideration of the optical shot noise of the sensor.

Next, in S303, the edge signal detection processing unit 203 detects the edge signal with respect to the input image. The edge signal detected at this time is hereinafter referred to as a first edge signal. The first edge signal is detected by applying the Laplacian filter shown in the equation of Equation 1 to each pixel of the input image. The filter output result for each pixel becomes the edge signal of the pixel, and the filter output results of all the pixels can be collectively used as the first edge signal of the input image.

Next, in S304, the noise suppression processing unit 204 performs noise suppression processing on the input image (reduced image) reduced by the reduction processing unit 201. The method of noise suppression processing is the same as the processing content of the noise suppression processing unit 202. The reduced image after noise suppression processing generated at this time is hereinafter referred to as a second NR image. Next, in S305, the edge signal detection processing unit 205 detects the edge signal for the reduced image. The method of detecting the edge signal is the same as the processing content of the edge signal detection processing unit 203. The edge signal detected at this time is hereinafter referred to as a second edge signal.

Although the processes from S301 to S305 have been described in order so far, the execution order of each step does not have to follow the description order of the flowchart of FIG. For example, S301 to S303 may be executed in parallel, and S304 and S305 may be executed in parallel after the reduced image is generated in S301.

Next, in S306, the edge signal correction processing unit 206 performs correction processing corresponding to the present embodiment on the second edge signal detected by the edge signal detection processing unit 205. The edge signal correction processing unit 206 outputs the value of the input signal as it is in the range where the magnitude of the input second edge signal is smaller than the predetermined value E according to the relationship shown in FIG. 4 (b). On the other hand, when the magnitude of the second edge signal exceeds the predetermined value, the value of the input signal is corrected to a value that does not exceed the predetermined value E. At this time, the greater the degree to which the value of the second edge signal exceeds the predetermined value E, the smaller the value can be corrected. Alternatively, in the range smaller than the predetermined value E, the output edge signal is corrected so as to increase as the magnitude of the input edge signal increases, and when the predetermined value E is exceeded, the output edge signal becomes smaller than the predetermined value E. It may be corrected as follows. In this way, the second edge signal obtained from the reduced image is corrected so that the signal value does not exceed the predetermined value E. Although the description is given with one polygonal line in the present embodiment, the correction method is not limited to this. For example, it suffices to have a characteristic of reducing the value of the output signal when the value of the input signal exceeds the predetermined value E. As an example, a non-linear form in which the output signal is not linearly reduced as shown in FIG. 4B but is gradually reduced may be used. Alternatively, the value exceeding the predetermined value E may be uniformly corrected so as to be a constant value (may include 0) equal to or less than the predetermined value.

Next, in S307, the enlargement processing unit 207 performs enlargement processing on the second NR image generated by the noise suppression processing in the noise suppression processing unit 204 by bilinear interpolation so as to have the same size as the input image. Next, in S308, the enlargement processing unit 208 performs enlargement processing on the second edge signal of the reduced image corrected by the edge signal correction processing unit 206 by bilinear interpolation so as to have the same size as the input image. The processing content of the enlargement processing unit 208 is the same as the processing content of the enlargement processing unit 207. The expanded edge signal obtained at this time is hereinafter referred to as a third edge signal.

Next, in S309, the composition ratio calculation processing unit 209 uses the image used by the image composition processing unit 210 from the first edge signal from the input image generated in S303 and the third edge signal generated in S308. Performs the calculation process of the synthesis ratio for synthesis. The composition ratio calculation processing unit 209 performs addition processing of the first edge signal and the third edge signal to generate a fourth edge signal used for calculating the composition ratio, and from this fourth edge signal, FIG. 4C is shown in FIG. The synthesis ratio is calculated according to the relationship shown in. In the present embodiment, the values corresponding to each pixel of the fourth edge signal are compared with the first threshold value TH1 and the second threshold value TH2. Then, if the edge amount of the pixel indicated by the fourth edge signal is equal to or less than the first threshold value, the composition ratio of the first NR image among the two images to be combined is set to 0%, and the composition of the second NR image is performed. The ratio is 100%. On the other hand, if it is larger than the second threshold value, it is set to 100% of the first NR image, and the composition ratio of the second NR image is set to 0%. In the range where the value of the fourth edge signal is larger than the first threshold value and is equal to or less than the second threshold value, the composition ratio is linearly calculated according to the edge amount.

As described above, in the present embodiment, the second edge signal is corrected so as to reduce the edge signal having a higher contrast than the predetermined value E, that is, the edge signal having high contrast that is also included in the first edge signal. Therefore, it is possible to effectively prevent the expansion of the edge signal around the high-contrast edge due to the enlargement processing of S308. Therefore, the compositing ratio calculated around the edge of high contrast can be reduced, and the compositing ratio of the reduced image from the low frequency range can be made superior. Here, an example in which the corrected second edge signal is enlarged to generate a third edge signal, and the third edge signal is combined with the first edge signal to generate a fourth edge signal. The explanation was given, but it is not limited to this. The second edge signal before the correction process is enlarged and combined with the first edge signal, and for the pixel whose value of the second edge signal exceeds the predetermined value E with respect to this edge signal, the pixel is The correction may be performed so as to lower the level of the corresponding edge signal. Alternatively, the gain based on the second edge signal before the correction processing is applied to the first edge signal to amplify the first edge signal, and the value of the second edge signal is a predetermined value E. For pixels exceeding the above, the gain may be set small. That is, when the value of the second edge signal exceeds the predetermined value E, the first edge signal may be corrected so that the degree of influence of the second edge signal is smaller than that when the value does not exceed the predetermined value E.

Next, in S310, the image composition processing unit 210 synthesizes the first NR image from the noise suppression processing unit 202 and the enlarged second NR image from the enlargement processing unit 207 according to the composition ratio calculated in S309. , The output signal of the noise suppression processing unit 200 for each band is generated. In the compositing process, the first NR image and the enlarged second NR image are weighted and added for each pixel according to the compositing ratio. By using this composition ratio, the resolution is maintained because the usage ratio of the first NR image is high where the edge amount is large, and the noise suppression because the usage ratio of the second NR image is high where the edge amount is small. The effect will be higher. Around the edge with high contrast, the first NR image is used for the part of the first edge signal, while the second NR image having a high noise suppression effect is used around the edge to reduce the noise step around the edge. Can be done.

According to the above embodiment, when calculating the composition ratio using the edge signal detected from the reduced image, the noise step around the high-contrast edge is made inconspicuous, but the edge resolution and flatness are obtained. It is possible to realize noise reduction processing that achieves both the noise suppression effect of the unit. In the above embodiment, an example of generating one reduced image with respect to the input image and synthesizing these two images has been described, but the description is not limited to this. The number of images to be generated may be 2 or more as long as a plurality of images having different frequency components included in each image are generated from one image and the plurality of images are combined. Absent. Further, as in the above-described embodiment, the reduced image has noise suppressed in the high frequency component as compared with the input image. Therefore, at least in the pixel in which the reduced image is synthesized, the noise in the high frequency component is suppressed as compared with the input image. Will decrease. Therefore, although the degree of the effect as noise reduction is reduced, the noise suppression processing unit can be omitted.

(Other Examples)
The present invention supplies a program that realizes one or more functions of the above-described embodiment to a system or device via a network or storage medium, and one or more processors in the computer of the system or device reads and executes the program. It is also possible to realize the processing. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

100: Digital camera, 101: Optical system, 102: Image sensor, 103: Pre-processing circuit, 104: A / D converter, 105: Image processing unit, 106: Control unit, 107: Display memory, 108: Display device , 109: Recording medium, 110: Operating member, 111: Bus

Claims (12)

A reduction means that reduces the input image and generates a reduced image,
A first detection means that performs edge detection on the input image and generates a first edge signal,
A second detection means that performs edge detection on the reduced image and generates a second edge signal,
A first noise suppression means for generating a first noise suppression image by performing noise suppression processing on the input image,
A second noise suppression means that performs noise suppression processing on the reduced image to generate a second noise suppression image,
A correction means that corrects the second edge signal and outputs the corrected edge signal.
An enlarging means for enlarging the corrected edge signal and the second noise-suppressed image and outputting the enlarged edge signal and the enlarged noise-suppressed image.
A calculation means that adds the enlarged edge signal and the first edge signal and calculates the composition ratio based on the value of the added edge signal.
A compositing means for compositing the first noise-suppressed image and the enlarged noise-suppressed image at the compositing ratio, and
With
When the value of the second edge signal exceeds a predetermined value, the correction means corrects the value of the second edge signal so that the value of the second edge signal does not exceed the predetermined value. ,
In the calculation means, the smaller the value of the edge signal after the addition, the higher the synthesis ratio of the noise suppression image after the enlargement, and the larger the value of the edge signal after the addition, the higher the first noise suppression image. An image processing device characterized by increasing the composition ratio of noise. The image according to claim 1 , wherein the correction means corrects the value of the second edge signal exceeding the predetermined value so that the value becomes smaller as the degree of exceeding the predetermined value increases. Processing equipment. The image processing apparatus according to claim 1 , wherein the correction means corrects the value of the second edge signal exceeding the predetermined value to a constant value equal to or less than the predetermined value. The calculation means is
If the value of the edge signal after the addition is less than the first threshold value, the combining ratio ratio of the noise suppressing image after the enlargement to 100%,
Wherein when the value of the addition after the edge signal is greater than the larger second threshold value than the first threshold value, according to the first noise suppression the combining ratio rate, wherein 100% and be Rukoto image The image processing apparatus according to any one of Items 1 to 3. A reduction means that reduces the input image and generates a reduced image,
A first detection means that performs edge detection on the input image and generates a first edge signal,
A second detection means that performs edge detection on the reduced image and generates a second edge signal,
A first noise suppression means for generating a first noise suppression image by performing noise suppression processing on the input image,
A second noise suppression means that performs noise suppression processing on the reduced image to generate a second noise suppression image,
An enlarging means for enlarging the second edge signal and the second noise-suppressed image and outputting the enlarged edge signal and the enlarged noise-suppressed image.
An addition means for adding the enlarged edge signal and the first edge signal, and
A correction means that corrects the edge signal output from the addition means and outputs the corrected edge signal,
A calculation means for calculating the composition ratio based on the corrected edge signal value, and
A compositing means for compositing the first noise-suppressed image and the enlarged noise-suppressed image at the compositing ratio, and
With
When the value of the second edge signal exceeds a predetermined value, the correction means corrects so as to lower the value of the edge signal output from the addition means.
In the calculation means, the smaller the value of the edge signal after the addition, the higher the synthesis ratio of the noise suppression image after the enlargement, and the larger the value of the edge signal after the addition, the higher the first noise suppression image. An image processing device characterized by increasing the composition ratio of noise. A reduction means that reduces the input image and generates a reduced image,
A first detection means that performs edge detection on the input image and generates a first edge signal,
A second detection means that performs edge detection on the reduced image and generates a second edge signal,
A first noise suppression means for generating a first noise suppression image by performing noise suppression processing on the input image,
A second noise suppression means that performs noise suppression processing on the reduced image to generate a second noise suppression image,
An enlarging means for enlarging the second noise-suppressed image and outputting the enlarged noise-suppressed image,
A correction means that applies a gain corresponding to the value of the second edge signal to the first edge signal, amplifies the first edge signal, and outputs the corrected edge signal.
A calculation means for calculating the composition ratio based on the corrected edge signal value, and
A compositing means for compositing the first noise-suppressed image and the enlarged noise-suppressed image at the compositing ratio, and
With
When the value of the second edge signal exceeds a predetermined value, the correction means adjusts the gain so that the degree of influence of the second edge signal becomes smaller than that when the value does not exceed the predetermined value. Set,
In the calculation means, the smaller the value of the corrected edge signal, the higher the composition ratio of the enlarged noise suppression image, and the larger the value of the corrected edge signal, the higher the first noise suppression image. An image processing device characterized by increasing the composition ratio of noise. The image processing apparatus according to any one of claims 1 to 6 , further comprising an imaging means for photographing a subject and generating the input image. Further provided with an input means for inputting the input image,
The image processing apparatus according to any one of claims 1 to 7 , wherein the input means reads the input image from a recording medium on which the input image is recorded and inputs the input image. A reduction process that reduces the input image and generates a reduced image,
A first detection step of performing edge detection on the input image to generate a first edge signal, and
A second detection step of performing edge detection on the reduced image to generate a second edge signal, and
A first noise suppression step of performing noise suppression processing on the input image to generate a first noise suppression image, and
A second noise suppression step of performing noise suppression processing on the reduced image to generate a second noise suppression image,
A correction step of correcting the second edge signal and outputting the corrected edge signal,
An enlargement step of enlarging the corrected edge signal and the second noise suppression image and outputting the enlarged edge signal and the enlarged noise suppression image.
A calculation step of adding the enlarged edge signal and the first edge signal and calculating the composition ratio based on the value of the added edge signal.
A compositing step of compositing the first noise-suppressed image and the enlarged noise-suppressed image at the compositing ratio,
Including
In the correction step, when the value of the second edge signal exceeds a predetermined value, the value of the second edge signal is corrected so that the value of the second edge signal does not exceed the predetermined value. ,
In the calculation step, the smaller the value of the edge signal after the addition, the higher the composition ratio of the enlarged noise suppression image, and the larger the value of the edge signal after the addition, the higher the first noise suppression image. An image processing method characterized by increasing the composition ratio of. A reduction process that reduces the input image and generates a reduced image,
A first detection step of performing edge detection on the input image to generate a first edge signal, and
A second detection step of performing edge detection on the reduced image to generate a second edge signal, and
A first noise suppression step of performing noise suppression processing on the input image to generate a first noise suppression image, and
A second noise suppression step of performing noise suppression processing on the reduced image to generate a second noise suppression image,
An enlargement step of enlarging the second edge signal and the second noise suppression image and outputting the enlarged edge signal and the enlarged noise suppression image.
An addition step of adding the enlarged edge signal and the first edge signal, and
A correction step of correcting the edge signal output in the addition step and outputting the corrected edge signal,
A calculation step of calculating the composition ratio based on the corrected edge signal value, and
A compositing step of compositing the first noise-suppressed image and the enlarged noise-suppressed image at the compositing ratio,
Including
In the correction step, when the value of the second edge signal exceeds a predetermined value, the value of the edge signal output in the addition step is corrected so as to be lowered.
In the calculation step, the smaller the value of the edge signal after the addition, the higher the composition ratio of the enlarged noise suppression image, and the larger the value of the edge signal after the addition, the higher the first noise suppression image. An image processing method characterized by increasing the composition ratio of. A reduction process that reduces the input image and generates a reduced image,
A first detection step of performing edge detection on the input image to generate a first edge signal, and
A second detection step of performing edge detection on the reduced image to generate a second edge signal, and
A first noise suppression step of performing noise suppression processing on the input image to generate a first noise suppression image, and
A second noise suppression step of performing noise suppression processing on the reduced image to generate a second noise suppression image,
An enlarging step of enlarging the second noise-suppressed image and outputting the enlarged noise-suppressed image, and
A correction step of applying a gain corresponding to the value of the second edge signal to the first edge signal, amplifying the first edge signal, and outputting the corrected edge signal.
A calculation step of calculating the composition ratio based on the corrected edge signal value, and
A compositing step of compositing the first noise-suppressed image and the enlarged noise-suppressed image at the compositing ratio,
Including
In the correction step, when the value of the second edge signal exceeds a predetermined value, the gain is adjusted so that the degree of influence of the second edge signal becomes smaller than that when the value does not exceed the predetermined value. Set,
In the calculation step, the smaller the value of the corrected edge signal, the higher the composition ratio of the enlarged noise suppression image, and the larger the value of the corrected edge signal, the higher the first noise suppression image. An image processing method characterized by increasing the composition ratio of. A program for operating a computer as each means of the image processing apparatus according to any one of claims 1 to 8.

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