JP2015033019A - Image processing device, image display device, program, and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing device capable of improving a detail feeling without enhancing a noise component.SOLUTION: An image processing device comprises: a second noise reduction processing unit (18) that reduces an amplitude which can be regarded as noise having small inter-frame correlation to generate a noise-reduced image from a target frame image; and a mixture processing unit (21) that generates an output frame image from the target frame image, the noise-reduced image, and a high-frequency component based on each pixel value of the target frame image and a maximum value and a minimum value in a block including a pixel of interest.

Description

  The present invention relates to an image processing apparatus, a program, and a recording medium that can improve the feeling of image detail without emphasizing noise components when performing image and video processing.

  When a still image or video is enlarged and displayed, even if the image quality is sharp enough for 1x display, the image quality may be blurred and the image quality may be blurred. is there. Therefore, it is possible to improve the sharpness by applying an enhancement process such as an unsharp mask process before the enlargement process. However, since the outline becomes thick or overshoot and undershoot occur around the outline, if an enlargement process is applied after the enhancement process, the image becomes very unnatural.

  Therefore, by adopting a mask having a small mask size such as 3 × 3 as the filter processing, it is possible to reduce the thickening of the contour. However, if the mask size is reduced, the frequency response of the filter becomes monotonous, so that the emphasis effect on unnecessary high frequency components becomes stronger than in the important frequency band. This problem will be described with reference to the drawings. 18A to 18C are diagrams illustrating examples of filter coefficients when a negative number of coefficients are arranged around the processing target image, and the frequency response thereof. The numerical value (1/16) before the mask shown in FIG. 18A is a number that is multiplied by all the numbers in the mask. A monotonically increasing characteristic is shown in which the gain (gain) increases as the frequency response increases. Since the frequency response is monotonous, if the enhancement effect on the contour component composed of the mid-frequency is enhanced, there arises a problem that an unnecessary high-frequency component containing a lot of noise is also enhanced.

  On the other hand, in Patent Document 1, a standard deviation is obtained from a difference in luminance value between a pixel of interest and each of other pixels, and an area with a large standard deviation such as a character or a line is subjected to an emphasis process using a high-pass filter. A method is described in which a smoothing process using a low-pass filter is performed on an area having a small standard deviation as shown in a picture to remove noise while maintaining the edge of the image. In Patent Document 1, three filters are proposed, and in each case, the effect as a high-pass filter is strong when the standard deviation is large, and the effect as a low-pass filter is strong when the standard deviation is small. Yes. Therefore, noise can be removed while maintaining the edge of the image.

JP 2009-266233 A (released on November 12, 2009)

  However, in the case of the method disclosed in Patent Document 1, the luminance difference between the target pixel and each of the other pixels is used, and the processing is based on the strength of the edge portion. Therefore, the noise component and the image detail component cannot be classified. Therefore, there is a problem that noise remains as detail and the detail is smoothed as noise.

  Therefore, the present invention has been made in view of the above problems, and an object of the present invention is to provide an image processing apparatus, an image display apparatus, a program, and a program capable of improving a detail feeling without enhancing noise components. It is to provide a recording medium.

  In order to solve the above-described problem, an image processing apparatus according to an aspect of the present invention is an image processing apparatus including a detail processing unit that brings a sense of detail to a frame image constituting a video, and the detail processing unit includes: An alignment unit for performing alignment between each pixel in the target frame image and its adjacent frame image, and reducing the amplitude that can be regarded as noise having a small inter-frame correlation using the aligned frame image, A noise reduction unit that generates a noise reduction image from an image, and a maximum value for calculating a maximum value and a minimum value of pixel values in the first block including the target pixel and its surrounding pixels for each pixel of the target frame image; For each pixel of the target frame image, the minimum value calculation unit, the pixel value of the target pixel, the maximum value calculated for the target pixel, and the maximum value A high-frequency component generation unit that calculates a high-frequency component based on the value; and a mixing unit that generates an output frame image based on the target frame image, the noise-reduced image, and the high-frequency component. .

  According to the above configuration, it is possible to perform image processing that improves the feeling of detail without enhancing the noise component. Note that it is difficult to determine whether it is a detail or noise by using only the information of the frame image alone. Therefore, it is an effective means to perform comparison between frame images as in the above configuration.

It is a block diagram which shows the structure of the television broadcast receiver of one embodiment of this invention. It is a block diagram which shows the structure of the video signal processing part which the said television broadcast receiver has. It is a block diagram which shows the structure of the detail feeling improvement process part which the said video signal process part has. It is a figure which shows the example of the alignment process which the alignment process part which the said detail feeling improvement process part has performs. It is a figure which shows the flowchart of the noise reduction process in the 2nd noise reduction process part which the said detail feeling improvement process part has. It is a figure which shows the attention pixel and its peripheral pixel in a 3x3 pixel window. It is a figure which shows the flowchart of the high frequency component production | generation process in the high frequency component production | generation process part which the said detail feeling improvement process part has. It is a figure for demonstrating the high frequency component production | generation process in the said high frequency component production | generation part. It is a figure which shows the flowchart of the mixing process which the mixing process part which the said detail feeling improvement process part has is performed. It is a figure which shows the example of the weighting coefficient table enhancementWeight and noiseWeight which use the dynamic range Range as an address. It is a block diagram which shows the structure of the detail feeling improvement process part of other embodiment of this invention. It is a figure which shows the flowchart of the noise reduction process in the 2nd noise reduction process part which the detail feeling improvement process part of said other embodiment has. It is a block diagram which shows the structure of the detail feeling improvement process part of another embodiment of this invention. It is a figure which shows the flowchart of the process in the high frequency process production | generation part which the detail feeling improvement process part of said another embodiment has. It is a block diagram which shows the structure of the detail feeling improvement process part of another embodiment of this invention. It is a block diagram which shows the structure of the monitor of other embodiment of this invention. It is a figure which shows the multi-display of another embodiment of this invention. It is a figure which shows the example of a filter coefficient when a negative number coefficient is arrange | positioned around the process target image, and its frequency response.

[Embodiment 1]
An embodiment of the present invention will be specifically described below with reference to the drawings. In the present embodiment, a television broadcast receiving apparatus 1 will be described as an example of the image display apparatus according to the present invention. Further, as an image processing apparatus according to the present invention, a video signal processing unit 42 included in the television broadcast receiving apparatus 1 will be described as an example. In the following embodiments, the video indicates a moving image.

(TV broadcast receiver)
FIG. 1 is a block diagram showing a configuration of a television broadcast receiving apparatus (image display apparatus) 1 according to the present embodiment. As shown in FIG. 1, the television broadcast receiving apparatus 1 includes an interface 2, a tuner 3, a control unit 4, a power supply unit 5, a display unit 6, an audio output unit 7, and an operation unit 8.

  The interface 2 includes a TV antenna 25, a DVI (Digital Visual Interface) terminal 22 for serial communication using a TMDS (Transition Minimized Differential Signaling) system, an HDMI (High-Definition multimedia Interface, registered trademark) terminal 23, a TCP (Transmission Control Protocol). ) Or a LAN terminal 24 for communication using a communication protocol such as UDP (User Datagram Protocol). The interface 2 transmits / receives data to / from an external device connected to the DVI terminal 22, the HDMI terminal 23, or the LAN terminal 24 in accordance with an instruction from the overall control unit 41.

  The tuner 3 is connected to the TV antenna 25, and a broadcast signal received by the TV antenna 25 is input to the tuner 3. The broadcast signal includes video data, audio data, and the like. In the present embodiment, the tuner 3 includes the terrestrial digital tuner 31 and the BS / CS digital tuner 32, but is not limited thereto.

  The control unit 4 includes an overall control unit 41 that comprehensively controls each block of the television broadcast receiving device 1, a video signal processing unit (image processing device) 42, an audio signal processing unit 43, and a panel controller 44.

  The video signal processing unit 42 performs predetermined processing on the video data input via the interface 9 and generates video data (video signal) to be displayed on the display unit 6.

  The audio signal processing unit 43 performs predetermined processing on the audio data input through the interface 9 to generate an audio signal.

  The panel controller 44 controls the display unit 6 to display the video of the video data output from the video signal processing unit 42 on the display unit 6.

  The power supply unit 5 controls electric power supplied from the outside. The overall control unit 41 causes the power supply unit 5 to supply power or shuts off the supply of power in accordance with an operation instruction input from the power switch of the operation unit 8. When the operation instruction input from the power switch is an operation instruction to switch on the power, when power is supplied to the entire television broadcast receiving apparatus 1 and the operation instruction input from the power switch is an operation instruction to switch off the power The electric power supplied to the television broadcast receiver 1 is cut off.

  The display unit 6 is, for example, a liquid crystal display (LCD), a plasma display panel, or the like, and displays a video of video data output from the video signal processing unit 42.

  The audio output unit 7 outputs the audio signal generated by the audio signal processing unit 43 under the instruction of the overall control unit 41.

  The operation unit 8 includes at least a power switch and a changeover switch. The power switch is a switch for inputting an operation instruction for instructing to switch the power of the television broadcast receiving apparatus 1 on and off. The change-over switch is a switch for inputting an operation instruction for designating a broadcast channel received by the television broadcast receiver 1. The operation unit 8 outputs an operation instruction corresponding to each switch to the overall control unit 41 in response to pressing of the power switch and the changeover switch.

  Note that an operation instruction corresponding to each switch may be transmitted to the television broadcast receiving apparatus 1 by providing the operation unit 8 in a remote controller capable of wirelessly communicating with the television broadcast receiving apparatus 1. In this case, the communication medium with which the remote controller communicates with the television broadcast receiver 1 may be wired or wireless.

(Video signal processor)
FIG. 2 is a block diagram illustrating a configuration of the video signal processing unit 42. As shown in FIG. 2, the video signal processing unit 42 includes a decoder 10, an IP conversion processing unit 11, a first noise reduction processing unit 12, a detail feeling improvement processing unit (detail processing unit) 13, a scaler processing unit 14, and a sharpness processing. Section 15 and a color adjustment processing section 16. In the present embodiment, each processing unit of the video signal processing unit 42 is described as processing RGB signals, but may be configured to process luminance signals.

  The decoder 10 decodes the compressed video stream to generate video data, and outputs the video data to the IP conversion processing unit 11. The IP conversion processing unit 11 converts the video data input from the decoder 10 from the interlace method to the progressive method as necessary. The first noise reduction processing unit 12 executes various types of noise reduction processing for reducing (suppressing) sensor noise included in video data output from the IP conversion processing unit 11 and compression artifacts generated during compression. To do.

  The detail improvement processing unit 13 performs a detail improvement process on the video data output from the first noise reduction processing unit 12 to provide a fine feeling even after the enlargement process. The scaler processing unit 14 performs a scaling process (enlargement process) according to the number of pixels of the display unit 6 on the video data output from the detail improvement processing unit 13. The sharpness processing unit 15 executes a sharpness process for sharpening the video of the video data output from the scaler processing unit 14. The color adjustment processing unit 16 performs color adjustment processing for adjusting contrast, saturation, and the like on the video data output from the sharpness processing unit 15.

  The video signal processing unit 42 appropriately stores video data when various processes are executed by the blocks of the video signal processing unit 42 in a storage unit (not shown).

  Here, the image data constituting the video data is configured in units of frames, and an image in units of frames is referred to as a frame image. Therefore, the video is composed of a plurality of frame images. In this specification, a frame image may be simply referred to as a frame.

(Detail feeling improvement processing section)
FIG. 3 is a block diagram showing a detailed configuration of the detail feeling improvement processing unit 13. The detail improvement processing unit 13 includes an alignment processing unit (positioning unit) 17, a second noise reduction processing unit (noise reduction unit) 18, a maximum value / minimum value calculation processing unit (maximum value / minimum value calculation unit) 19. The high frequency component generation processing unit (high frequency component generation unit) 20 and the mixing processing unit (mixing unit) 21 are provided.

The alignment processing unit 17 executes alignment processing for aligning pixels between frames. Specifically, for each input pixel, the alignment processing unit 17 calculates the difference absolute value sum SAD (Sum) between the processing target frame (target frame image) N and the previous frame (adjacent frame image) N−1. of absolute difference) is searched for the pixel position of the previous frame N-1. The difference absolute value sum SAD calculates the sum of absolute differences of pixels in a P × Q pixel window centered on the pixel for which the difference absolute value sum SAD is calculated. When the pixel coordinate position of the processing target frame N is (y _n , x _n ) and the pixel position of the previous frame N-1 is (y _n−1 , x _n−1 ), the difference absolute value sum SAD of both is It is computable as following formula (1).

When the search range of the pixel position where the difference absolute value sum SAD is the minimum is I × J, the minimum difference absolute value sum between the processing target frame N and the previous frame N−1 at the pixel position (y, x). minSAD _N-1 (y, x) can be calculated according to the following equation (2).

In addition, coordinates (y + i, x + j) satisfying the above equation (2) are obtained as coordinates (motY _N−1 , motX _N−1 ) that minimize the sum of absolute differences.

Similarly, the minimum difference absolute value sum minSAD _{N + 1} (y, x) between the processing target frame N at the pixel position (y, x) and the subsequent frame (adjacent frame image) N + 1 is expressed by the following equation (3). It can be calculated as follows.

Also, coordinates (y + i, x + j) satisfying the above equation (3) are obtained as coordinates (motY _{N + 1} , motX _{N + 1} ) that minimize the sum of absolute differences.

FIG. 4 is a diagram illustrating an example of the alignment process. The difference absolute value sum SAD calculation window size P × Q is 5 × 5, and the pixel position search range is I × J 3 × 3. Between the processing target frame N and the previous frame N−1 The figure explaining the calculation method of difference absolute value sum total SAD of is shown. A search range consisting of 3 × 3 pixel positions of the previous frame N−1 where the sum of absolute differences SAD is minimum with respect to 5 × 5 pixels centering on IN _N (y, x) in the processing target frame N; That is, (y-1, x-1), (y-1, x), (y-1, x + 1), (y, x-1), (y, x), (y, x + 1 ), (Y + 1, x−1), (y + 1, x), and (y + 1, x + 1) are searched from a total of nine pixels. 4A shows 5 × 5 pixels centering on IN _N (y, x) in the processing target frame N, and FIG. 4B shows IN _N−1 (y in the previous frame N−1. -1, x-1) as a center pixel and its peripheral pixels.

The second noise reduction processing unit 18 performs noise reduction processing for reducing, as noise, a minute amplitude (amplitude that can be regarded as noise) having a small (low) correlation between frames using the aligned frames. Specifically, the second noise reduction processing unit 18 includes the minimum difference absolute value sum minSAD _N−1 (y, x), minSAD _{N + 1} (y, x) calculated by the alignment processing unit 17, and Filtering is performed in the time axis direction using the coordinates (motY _N−1 , motX _N−1 ) and (motY _{N + 1} , motX _{N + 1} ) that minimize the sum of absolute differences. As described above, after the alignment processing unit 17 performs alignment between a plurality of frames, the second noise reduction processing unit 18 performs filter processing, thereby obtaining a small amplitude with a small inter-frame correlation. It can be reduced as noise.

FIG. 5 is a diagram illustrating a flowchart of noise reduction processing in the second noise reduction processing unit 18. First, the second noise reduction processing unit 18 uses the minimum absolute difference sum minSAD _N-1 (y, x) and minSAD _{N + 1} (y, x) to perform weighting for filtering in the time axis direction. A coefficient is calculated (step 1 and the subsequent steps are omitted as S1). The weighting coefficient in the previous frame N-1 is smaller as the minimum value minSAD _N-1 (y, x) of the difference absolute value sum SAD between the processing target frame N and the previous frame N-1 is larger. Calculate as follows. For example, the weighting coefficient of the previous frame N-1 can be calculated by the following equation (4). As the minimum value of the difference absolute value sum SAD is larger, the difference between both frames is larger, that is, the correlation between frames is smaller.

In the above equation (4), when minSAD _N-1 (y, x) is smaller than a threshold TH_SAD_UPLIMIT (for example, 2048), it is obtained by normalizing minSAD _N-1 (y, x) by WNR_NORM (for example, 256). A value obtained by applying the value to the function f (x) = 1 / (1 + x) is multiplied by a predetermined weight coefficient TH_WNR_RATIO _N-1 (for example, 1.0) to obtain a weight coefficient wNR _N-1 . On the other hand, when minSAD _N-1 (y, x) is equal to or greater than the threshold value TH_SAD_UPLIMIT, a weight coefficient TH_WEIGHT_INIT (for example, 0) is used.

For the processing target frame N, a predetermined weight coefficient TH_WNR_RATIO _N (for example, 1.0) is used as it is as the weight coefficient wNR _N as shown in the following equation (5).

The weight coefficient of the subsequent frame N + 1 is the minimum value minSAD _{N + 1} (y, x) of the difference absolute value sum SAD between the processing target frame N and the subsequent frame N + 1 in the same manner as the weight coefficient of the previous frame N-1. Can be calculated by the following equation (6).

Next, the second noise reduction processing unit 18 uses the weighting coefficient obtained for each frame, the pixel value IN _N (y, x) at the coordinates (y, x) of the pixel in the processing target frame N, and the position The combined pixel value IN _N-1 (motY _N−1 , motX _N−1 ) in the previous frame N−1 and pixel value IN _{N + 1} (motY _{N + 1} , motX _{N + 1} ) in the subsequent frame N + 1 are combined. Are mixed to execute a time-axis filtering process for calculating a noise reduction processing result (noise reduction image) NR _N (y, x) (S2). The calculation of the noise reduction processing result NR _N (y, x) is as shown in the following equation (7).

The maximum value / minimum value calculation processing unit 19 for each pixel (input pixel) in the frame, a pixel value (pixel density) in an m × n (for example, 3 × 3) pixel window (first block) centered on the pixel of interest. Value) is calculated. FIG. 6 is a diagram illustrating a pixel of interest and its peripheral pixels when m = n = 3 as an example. The maximum value maxVal _N in the m × n pixel window centered on the pixel of interest is calculated as the following formula (8) with reference to the surrounding pixels.

Here, IN (y, x) represents the pixel value (density value in the present embodiment) of the pixel at the coordinates (y, x) of the input image (input image data). The pixel value is a value represented by 0 to 255 when the input image is represented by 8 bits, for example. Similarly, the minimum value minVal _N in the m × n pixel window centered on the target pixel is calculated as the following formula (9) with reference to the surrounding pixels.

  The high frequency component generation processing unit 20 performs high frequency component generation processing for generating a high frequency component using the input image and the maximum value and the minimum value in the m × n window calculated by the maximum value / minimum value calculation processing unit 19. Do. FIG. 7 is a flowchart of the high frequency component generation process. First, the high frequency component generation processing unit 20 calculates the absolute difference diffMax between the pixel value (input pixel value) of the input image and the maximum value in the m × n window according to the following equation (10) (S3).

However, | · | means absolute value calculation.

  Similarly, the absolute difference value diffMin is calculated according to the following equation (11) (S4).

  Next, the high frequency component generation processing unit 20 multiplies the absolute difference diffMax from the maximum value and the absolute difference diffMin from the minimum value by a predetermined coefficient (constant) TH_RANGE (for example, 1.5). Compare (S5). If the difference absolute value diffMax from the maximum value is larger than the multiplication result of the difference absolute value diffMin from the minimum value and TH_RANGE (YES in S5), the high frequency component Enh is calculated as shown in the following equation (12) (S6). ).

  On the other hand, if the difference absolute value diffMax from the maximum value is equal to or less than the result of multiplying the difference absolute value diffMin from the minimum value by TH_RANGE (NO in S5), the difference absolute value diffMin from the minimum value and the maximum value The result obtained by multiplying the absolute difference value diffMax by a predetermined coefficient (constant) TH_RANGE (for example, 1.5) is compared (S7). If the difference absolute value diffMin from the minimum value is larger than the multiplication result of the difference absolute value diffMax from the maximum value and TH_RANGE (YES in S7), the high frequency component Enh is calculated as shown in the following equation (13) (S8). ).

  On the other hand, if the difference absolute value diffMin from the minimum value is equal to or less than the multiplication result of the difference absolute value diffMax from the maximum value and TH_RANGE (NO in S7), the high frequency component Enh is set to 0 as shown in the following equation (14). (S9).

FIG. 8 is a diagram for explaining the high-frequency component generation processing. (A) of FIG. 8 shows the input pixel value and the maximum value maxVal in the m × n window when the difference absolute value diffMax from the maximum value is larger than the multiplication result of the difference absolute value diffMin from the minimum value and TH_RANGE. _N , m × n in-window minimum value minVal _N , difference absolute value diffMax from maximum value, difference absolute value diffMin from minimum value, and high frequency component Enh are shown. Similarly, FIG. 8B shows an input pixel value in the m × n window when the difference absolute value diffMin from the minimum value is larger than the multiplication result of the difference absolute value diffMax from the maximum value and TH_RANGE. The relationship among the maximum value maxVal _N , the m × n minimum value minVal _{N in the} window, the absolute difference value diffMax from the maximum value, the absolute difference value diffMin from the minimum value, and the high frequency component Enh is shown.

  In the case of FIG. 8A, the high frequency component is generated by subtracting the difference absolute value diffMax from the maximum value from the input pixel value having a value close to the minimum value, so that the dynamic range can be expanded. Becomes sudden and the detail feeling can be improved. In the case of FIG. 8B, the high frequency component can be generated by adding the difference absolute value diffMin from the minimum value to the input pixel value having a value close to the maximum value, and the dynamic range can be expanded. Becomes sudden and the detail feeling can be improved.

  On the other hand, if the difference absolute value diffMax from the maximum value is equal to or less than the result of multiplication of the difference absolute value diffMin from the minimum value and TH_RANGE, and the difference absolute value diffMin from the minimum value is the difference absolute value diffMax from the maximum value When the result is equal to or less than the multiplication result of TH_RANGE, the pixel value of the input image has a value near the middle between the minimum value and the maximum value. For this reason, if an input image having a value near the middle is emphasized in any direction, the pixel value is divided into a pixel value near the minimum value and a pixel value near the maximum value, and the sense of detail is lost. End up. Therefore, the high frequency component Enh is set to 0 in order to prevent the sense of fineness from being lost.

  The mixing processing unit 21 mixes the input image, the noise reduction processing result generated by the second noise reduction processing unit 18, and the high frequency component generated by the high frequency component generation processing unit 20 to improve the feeling of detail. Mixing is performed.

  FIG. 9 is a diagram illustrating a flowchart of the mixing process. First, the mixing processing unit 21 calculates a dynamic range Range that is a difference value between the maximum value and the minimum value in a K × L (for example, 5 × 5) pixel window (second block) centered on the target pixel by the following equation (15). ) (S10).

  Next, the blending processing unit 21 refers to the weighting coefficient table (first weighting coefficient) enhancementWeight using the dynamic range Range as an address, and the return value (enhanceWeight [Range]) and the high frequency component generation processing unit 20 calculate it. The multiplication result with the high frequency component Enh is calculated as the enhancement amount wEnh (S11).

Then, in order to avoid noise enhancement by mixing high frequency components, a penalty amount (noise penalty, adjustment amount) Reduction due to noise is calculated using a difference value between the input image and the noise reduction processing result. (S12). The penalty amount Reduction is a weighting coefficient table (first order) with the absolute value of the difference between the input pixel value IN _N (y, x) in the processing target frame N and the noise reduction processing result NR _N (y, x) as the dynamic range Range. 2) (weighting factor 2) noiseWeight, and multiplying the return value (weightLUT [range]).

Finally, the mixing processing unit 21 adds and subtracts the penalty amount Reduction in consideration of the sign of the enhancement amount wEnh and adds it to the noise reduction processing result NR _N (y, x) as shown in the following equation (17). Then, a mixed calculation process for calculating a final process result (output frame image) Result is performed (S13).

In the above equation (17), instead of adding to the noise reduction processing result NR _N (y, x), it may be added to the input pixel value IN _N (y, x), or the noise reduction processing result NR _N ( y, x) and the input pixel value iN _N (y, may be added to a mixture of a x) at a predetermined ratio.

  FIGS. 10A and 10B are diagrams illustrating examples of weight coefficient tables enhancementWeight and noiseWeight having the dynamic range Range as an address, respectively. These are stored in a storage unit (not shown). For an image area with a relatively narrow dynamic range, excluding an image area with an extremely small dynamic range where noise is conspicuous by setting enhanceWeight as shown in FIG. By increasing the weighting coefficient, it is possible to obtain a high detail feeling improvement effect. Furthermore, by reducing the weighting coefficient for an image region with a wide dynamic range, only the feeling of detail can be improved without causing overshoot or undershoot. Also, by setting the noiseWeight as shown in FIG. 10B, if there is a small amplitude with small correlation between frames in an image region with a small dynamic range where noise is conspicuous, the noise is increased by increasing the penalty amount. Can be suppressed from being emphasized.

  By the above processing, a high frequency component can be created effectively, and the feeling of detail can be improved without enhancing the noise component. The above processing is performed for all input pixels.

  Here, if the outline emphasis process is performed before the enlargement process by the scaler processing unit 14, the emphasized outline segment is enlarged as it is. As a result, there is a problem that the contour line segment after enlargement looks thick and looks unnatural in a natural image. On the other hand, for detail components that give a sense of detail, if the detail is not strengthened before enlargement processing, the high-frequency components that are the source of detail will be lost in the interpolation processing of enlargement processing, and the high-frequency components will be removed after enlargement processing. It becomes difficult to emphasize and improve the detail feeling. Therefore, in this embodiment, before the high frequency component is impaired by the interpolation calculation in the enlargement process, the detail feeling improvement process is performed to improve the detail feeling, and the sharpness process is performed after the enlargement process, thereby thickening the contour. The sense of fineness can be improved while improving the sharpness.

[Embodiment 2]
In the video signal processing unit and the television broadcast receiving apparatus according to the present embodiment, the detail feeling improvement processing unit 13 of the video signal processing unit 42 according to the first embodiment shown in FIG. (Processing section) 13a. In the video signal processing unit and the television broadcast receiving apparatus of the present embodiment, the configuration other than the detail feeling improvement processing unit 13a is the same as that of the video signal processing unit 42 and the television broadcast receiving apparatus 1 of the first embodiment. Therefore, the same components as those described in the first embodiment are denoted by the same reference numerals, and description of the configurations and processes described in the first embodiment is omitted.

As shown in FIG. 11, the detail improvement processing unit 13a includes an alignment processing unit 17a, a second noise reduction processing unit 18a, a maximum / minimum value calculation processing unit 19, a high frequency component generation processing unit 20, and a mixing processing unit 21. Consists of. The detail improvement processing unit 13a uses the pixel value NR _N of the noise reduction processing result in the previous frame N-1 instead of using the input pixel value IN _N-1 of the previous frame N-1 as the pixel value in the previous frame N-1. _-1 is different from the detail improvement processing unit 13 described with reference to FIG. 3 in the first embodiment.

For each input pixel, the alignment processing unit 17a uses the noise reduction processing result NR _N-1 in the previous frame N-1 instead of the input pixel value IN _N-1 in the previous frame _N-1, and uses the processing target frame N And the previous frame N−1 are searched for the pixel position of the previous frame N−1 where the difference absolute value sum SAD is minimum. When the search range of the pixel position where the difference absolute value sum SAD is the minimum is I × J, the minimum difference absolute value sum between the processing target frame N and the previous frame N−1 at the pixel position (y, x). minSAD _N-1 (y, x) can be calculated according to the following equation (18).

In addition, coordinates (y + i, x + j) satisfying the above equation (18) are obtained as coordinates (motY _N−1 , motX _N−1 ) that minimize the sum of absolute differences. On the other hand, the minimum difference absolute value sum minSAD _{N + 1} (y, x) between the processing target frame N and the subsequent frame N + 1 at the pixel position (y, x), and the coordinates (motY _{N + 1} , motX _{N + 1} ) can be calculated by the same method as in the first embodiment.

Similar to the second noise reduction processing unit 18 of the first embodiment, the second noise reduction processing unit 18a is calculated between the processing target frame N and the previous frame N-1 calculated by the alignment processing unit 17. Minimum difference absolute value sum minSAD _N-1 (y, x), minimum difference absolute value sum minSAD _{N + 1} (y, x) between the processing target frame N and the subsequent frame N + 1, and the difference absolute value sum is minimum Using the coordinates (motY _N−1 , motX _N−1 ) and (motY _{N + 1} , motX _{N + 1} ), the filter processing is performed in the time axis direction. As described above, after the alignment between the plurality of frames is performed by the alignment processing unit 17, the second noise reduction processing unit 18 performs the filtering process so that a small amplitude having a small inter-frame correlation is used as noise. Can be reduced.

FIG. 12 is a diagram illustrating a flowchart of the noise reduction processing in the second noise reduction processing unit 18a of the present embodiment. It differs from the noise reduction processing described in Embodiment 1 with reference to FIG. 5 in that it includes a weighting factor update processing based on history information. First, the second noise reduction processing unit 18a performs the minimum difference absolute value sum minSAD _N-1 (y, x), minSAD _{N + 1} (y, x), in the same manner as the process described with reference to FIG. The weight coefficients wNR _N−1 , wNR _N , and wNR _{N + 1} for adding the pixel values in the time axis direction are calculated (S1).

Next, the weighting factor wNR _N-1 of the previous frame _N-1 is updated using the processing history information up to the previous frame (S21). First, it is assumed that the processing history information controlNR is initialized to a predetermined threshold TH_CONTROL_INIT (for example, 1.0), and the minimum difference absolute value sum minSAD _N-1 (y, x) is expressed as shown in the following equation (19). If it is smaller than a predetermined threshold TH_SAD_ACCEPT (for example, 400), the controlNR is updated so that the value of controlNR becomes larger according to the value of the minimum difference absolute value sum minSAD _N-1 (y, x). Conversely, if the minimum difference absolute value sum minSAD _N-1 (y, x) is greater than or equal to TH_SAD_ACCEPT, there is no correlation between the processing target frame N and the previous frame N-1 at the coordinates (y, x). And the value of the processing history information controlNR (y, x) is reset to TH_CONTROL_INIT. For example, the history information controlNR is a value obtained by multiplying the ratio of the sum of the weight coefficients for each frame calculated in the weight coefficient calculation process and the weight coefficient in the previous frame N−1 by a predetermined coefficient TH_RATIO_UPDATE (for example, 1.0). Add and update.

As shown in the following equation (20), by multiplying the weight coefficient wNR _N-1 of the previous frame N-1 by the updated history information controlNR (y, x), the processing history information up to the immediately preceding frame is used, The weight coefficient wNR _N-1 of the previous frame N- ₁ is updated.

Finally, the second noise reduction processing unit 18a is aligned with the pixel value IN _N (y, x) at the coordinates (y, x) in the processing target frame N using the weighting coefficient obtained for each frame. , The pixel value NR _N-1 (motY _N−1 , motX _N−1 ) in the previous frame N−1 and the pixel value IN _{N + 1} (motY _{N + 1} , motX _{N + 1} ) in the subsequent frame N + 1 are mixed. As a result, the time axis filter processing for calculating the noise reduction processing result NR _N (y, x) is executed (S2). The calculation of the noise reduction processing result NR _N (y, x) is as shown in the following equation (21).

  Similarly to the processing described in the first embodiment, the maximum value / minimum value calculation processing unit 19 uses the maximum value in an m × n (for example, 3 × 3) pixel window centered on the target pixel for each input pixel, And the minimum value is calculated. Also for the high frequency component generation processing unit 20, the input image, the maximum value in the m × n window calculated by the maximum value / minimum value calculation processing unit 19, and the minimum, as in the processing described in the first embodiment. A high frequency component is generated using the value. Similarly to the processing described in the first embodiment, the mixing processing unit 21 also uses the input image, the noise reduction processing result generated by the second noise reduction processing unit 18a, and the high frequency component generation processing unit 20. The generated high frequency components are mixed to improve the detail feeling.

  Through the above processing, the detail improvement processing according to the present embodiment can reflect the noise reduction processing result in the previous frame of the processing target frame N as compared with the detail improvement processing according to the first embodiment. Reduction performance can be further improved.

[Embodiment 3]
In the video signal processing unit and the television broadcast receiving apparatus according to the present embodiment, the detail improvement processing unit 13 of the video signal processing unit 42 according to the first embodiment shown in FIG. (Processing unit) 13b. In the video signal processing unit and the television broadcast receiving apparatus of the present embodiment, the configuration other than the detail improvement processing unit 13b is the same as that of the video signal processing unit 42 and the television broadcast receiving apparatus 1 of the first embodiment. Therefore, the same components as those described in the first embodiment are denoted by the same reference numerals, and description of the configurations and processes described in the first embodiment is omitted.

  As shown in FIG. 13, the detail feeling improvement processing unit 13b includes an alignment processing unit 17, a second noise reduction processing unit 18, a maximum / minimum value calculation processing unit 19A, a high frequency component generation processing unit 20b, and a mixing process. A portion 21b is provided. The detail feeling improvement processing unit 13b generates a high frequency component using not only the processing target frame N but also the maximum value and the minimum value in the m × n window in the aligned previous frame N−1 and the subsequent frame N + 1. This is different from the detail improvement processing unit 13 described with reference to FIG.

  Similar to the processing described in the first embodiment, the alignment processing unit 17 determines the difference between the minimum value and the difference of the absolute difference sum SAD between the processing target frame N and the previous frame N−1 for each input pixel. The pixel position where the absolute value sum SAD is minimum is calculated. Further, between the processing target frame N and the subsequent frame N + 1, a pixel position where the minimum value of the difference absolute value sum SAD and the difference absolute value sum SAD are minimum is calculated.

Similar to the processing described in the first embodiment, the second noise reduction processing unit 18 calculates the absolute value of the minimum difference between the processing target frame N and the previous frame N−1 calculated by the alignment processing unit 17. The sum total minSAD _N-1 (y, x), minSAD _{N + 1} (y, x) between the processing target frame N and the subsequent frame N + 1, and the coordinates (motY _N-1 , Using motX _N-1 ) and (motY _{N + 1} , motX _{N + 1} ), the small amplitude with a small inter-frame correlation is reduced as noise by adding in the time axis direction. In this way, after performing alignment between a plurality of frames by the alignment processing unit 17, the second noise reduction processing unit 18 performs time axis filter processing, thereby obtaining a small amplitude with small inter-frame correlation. It can be reduced as noise.

  The maximum value / minimum value calculation processing unit 19A includes a pixel of interest and a surrounding pixel for each pixel of the processing target frame N and the aligned pixels of the previous frame N-1 and the subsequent frame N + 1. It is a block which calculates the maximum value and the minimum value of the pixel value in the. The maximum value / minimum value calculation processing unit 19A is a first maximum value / minimum value calculation processing unit 19a that calculates the maximum value and the minimum value in the m × n pixel window centered on the target pixel of the processing target frame N, and the processing target. A second maximum value / minimum value calculation processing unit 19b for calculating a maximum value and a minimum value in an m × n pixel window centered on the target pixel of the previous frame N−1 aligned with the frame N; A third maximum value / minimum value calculation processing unit 19c that calculates the maximum value and the minimum value in the m × n pixel window centered on the target pixel of the frame N + 1 after being aligned with the target frame N is provided.

  The first maximum value / minimum value calculation processing unit 19a is similar to the maximum value / minimum value calculation processing unit 19 described with reference to FIG. The maximum value and the minimum value in the xn (for example, 3 × 3) pixel window are calculated.

The second maximum value / minimum value calculation processing unit 19b uses the coordinates (motY _N−1 , motX _N−1 ) where the sum of absolute differences is minimum as shown in the following formula (22). For each input pixel at _N−1 , a maximum value maxVal _N−1 in an m × n (for example, 3 × 3) pixel window centered on the pixel of interest is calculated.

Similarly, the minimum value minVal _N−1 in the m × n pixel window centered on the target pixel is calculated as the following equation (23).

The third maximum value / minimum value calculation processing unit 19c, after the alignment, is performed using the coordinates (motY _{N + 1} , motX _{N + 1} ) that minimize the sum of the absolute differences as shown in the following equation (24). For each input pixel at _{N + 1} , the maximum value maxVal _{N + 1} in an m × n (for example, 3 × 3) pixel window centered on the pixel of interest is calculated.

Similarly, the minimum value minVal _{N + 1} in the m × n pixel window centered on the target pixel is calculated as in the following formula (25).

  The high-frequency component generation processing unit 20b receives the maximum value in the m × n window in each frame calculated by the input image, the first, second, and third maximum / minimum value calculation processing units 19a, 19b, and 19c. A high frequency component is generated using the minimum value. The high frequency component generation processing unit 20b generates a high frequency component (first high frequency component) in each frame according to the flowchart shown in FIG.

First, a high frequency component is calculated for each frame (S31). High-frequency component Enh _N in the processing target frame N, respectively, the DiffMax _N as DiffMax, using DiffMin _N as DiffMin, can be calculated according to the flowchart shown in FIG. The difference absolute value diffMax from the maximum value is compared with the result obtained by multiplying the difference absolute value diffMin from the minimum value by a predetermined coefficient TH_RANGE (for example, 1.5), and the difference absolute value diffMax from the maximum value is the minimum If the absolute value of the difference is larger than the multiplication result of the absolute value diffMin and TH_RANGE, the high frequency component Enh is calculated as in the following equation (26).

  On the other hand, when the difference absolute value diffMax from the maximum value is equal to or less than the multiplication result of the difference absolute value diffMin and TH_RANGE, the difference absolute value diffMin from the minimum value and the difference absolute value diffMax from the maximum value are set to a predetermined coefficient TH_RANGE (for example, , 1.5) is compared with the result. If the difference absolute value diffMin from the minimum value is larger than the multiplication result of the difference absolute value diffMax from the maximum value and TH_RANGE, the high frequency component Enh is calculated as in the following equation (27).

  On the other hand, when the difference absolute value diffMin from the minimum value is equal to or less than the multiplication result of the difference absolute value diffMax and TH_RANGE, the high frequency component Enh is set to 0 as shown in the following equation (28).

For even a high-frequency component Enh _N-1 in the previous frame N-1, respectively, the diffMax _N-1 as DiffMax, using diffMin _N-1 as DiffMin, calculated according to the flowchart shown in FIG. Further, the high-frequency component Enh _{N + 1} in the subsequent frame N + 1 also respectively, the DiffMax _{N + 1} as DiffMax, using DiffMin _{N + 1} as DiffMin, calculated according to the flowchart shown in FIG.

Next, the high frequency component generation processing unit 20b calculates a weighting factor for the high frequency component of each frame (S32). In the same manner as the second noise reduction processing unit 18, the high frequency components are added in the time axis direction using the minimum difference absolute value sum minSAD _N-1 (y, x) and minSAD _{N + 1} (y, x). The weight coefficient is calculated. The weighting coefficient in the previous frame N-1 is smaller as the minimum value minSAD _N-1 (y, x) of the difference absolute value sum SAD between the processing target frame N and the previous frame N-1 is larger. Calculate as follows. For example, the weighting coefficient of the previous frame N-1 is calculated as the following formula (29).

In the above equation (29), the value obtained by normalizing minSAD _N-1 (y, x) with WENH_NORM (for example, 256) is applied to the function f (x) = 1 / (1 + x). Then, a predetermined weight coefficient TH_WENH_RATIO _N-1 (for example, 1.0) is multiplied to obtain a weight coefficient wENH _N-1 . For the processing target frame N, a predetermined weight coefficient TH_WENH_RATIO _N (for example, 1.0) is used as the weight coefficient wENH _N as it is as in the following equation (30).

The weight coefficient of the subsequent frame N + 1 is the minimum value minSAD _{N + 1} (y, x) of the difference absolute value sum SAD between the processing target frame N and the subsequent frame N + 1 in the same manner as the weight coefficient of the previous frame N-1. Is calculated as shown in the following formula (31).

  Finally, the high frequency component generation processing unit 20b uses the weighting coefficient obtained for each frame and mixes with the high frequency component in each frame as shown in the following equation (32), thereby obtaining the final high frequency component (second A high frequency component mixing process for calculating (high frequency component) is performed (S33).

  Similar to the processing in the first embodiment, the mixing processing unit 21b mixes the input image, the noise reduction processing result, and the high-frequency component generated by the high-frequency component generation processing. However, in the flowchart of the mixing process illustrated in FIG. 9, the dynamic range that is the difference value between the maximum value and the minimum value in a K × L (for example, 5 × 5) pixel window centered on the target pixel in the processing target frame N. Instead of calculating the range, the maximum dynamic range among the processing target frame N, the previous frame N−1, and the subsequent frame N + 1 is calculated as the range as shown in the following equation (33). This is different from the mixing processing unit 21 shown in FIG.

  Through the above processing, the detail feeling improvement processing unit 13b of the present embodiment can create a high frequency component in consideration of the inter-frame correlation. Therefore, flicker caused by variations in the amount of enhancement between frames can be reduced.

[Embodiment 4]
In the video signal processing unit and the television broadcast receiving apparatus according to the present embodiment, the detail feeling improvement processing unit 13 of the video signal processing unit 42 according to the first embodiment shown in FIG. (Processing section) 13c. In the video signal processing unit and the television broadcast receiving apparatus of the present embodiment, the configuration other than the detail feeling improvement processing unit 13c is the same as that of the video signal processing unit 42 and the television broadcast receiving apparatus 1 of the first embodiment. Therefore, the same components as those described in the first embodiment are denoted by the same reference numerals, and description of the configurations and processes described in the first embodiment is omitted.

  The detail feeling improvement processing unit 13c of the present embodiment is configured by combining the detail feeling improvement processing unit 13a shown in FIG. 11 and the detail feeling improvement processing unit 13b shown in FIG. As shown in FIG. 15, the detail improvement processing unit 13c includes an alignment processing unit 17a, a second noise reduction processing unit 18a, a maximum / minimum value calculation processing unit 19B, a high frequency component generation processing unit 20b, and a mixing processing unit 21b. Is provided. The maximum value / minimum value calculation processing unit 19B includes a first maximum value / minimum value calculation processing unit 19a, a second maximum value / minimum value calculation processing unit 19b ', and a third maximum value / minimum value calculation processing unit 19c.

Details of the processing of the detail feeling improvement processing unit 13c are the same as the contents of the processing of the detail feeling improvement processing unit 13a and the detail feeling improvement processing unit 13b. Therefore, explanation is omitted. As can be seen from FIG. 15, the second maximum value / minimum value calculation processing unit 19b ′ receives the previous frame N in the second maximum value / minimum value calculation processing unit 19b as the pixel value in the previous frame N-1. Instead of the input pixel value IN _N-1 of -1, the pixel value NR _N-1 of the noise reduction processing result in the previous frame _N-1 is input.

  Through the above processing, the detail improvement processing unit 13c of the present embodiment can reflect the noise reduction processing result in the previous frame of the processing target frame N. Therefore, the noise reduction performance can be improved, and The high frequency component can be created in consideration of the inter-frame correlation. Therefore, flicker due to variation in the amount of enhancement between frames can be reduced.

[Embodiment 5]
In the first to fourth embodiments described above, the case where the image processing apparatus according to the present invention is applied to a video signal processing unit of a television broadcast receiving apparatus having a tuner has been described as an example. In this embodiment, a configuration in which the image processing apparatus according to the present invention is applied to a processing unit that executes video signal processing of a monitor (information display) that does not have a tuner will be described.

  FIG. 16 is a block diagram showing the configuration of the monitor (image display device) 110 of the present embodiment. In addition, about the same structure as the member demonstrated in Embodiment 1-4, the same member number is attached | subjected and description is abbreviate | omitted.

  As shown in FIG. 16, the monitor 110 includes an interface 200, a control unit 4, a power supply unit 5, a display unit 6, an audio output unit 7, and an operation unit 8. The interface 200 is for connecting to peripheral devices, and generally includes an interface for connecting to the DVI terminal 22, the HDMI terminal 23, and the LAN terminal 24 in addition to the D-sub connector 111. . The control unit 4 includes a video signal processing unit 42 that performs predetermined processing on video data input through the interface 200, an audio signal processing unit 43 that performs predetermined processing on audio data input through the interface 200, and a device An overall control unit 41 that performs control and a panel controller 44 that controls display on the display unit 6 are provided. Since the image processing apparatus according to the present invention is applied to the video signal processing unit 42 of the monitor 110, the monitor 110 can execute processing for improving the sense of details of video with high quality.

[Embodiment 6]
In the first to fifth embodiments, the image processing apparatus according to the present invention has one display unit 6, that is, a case where it is applied to a video signal processing unit of a television broadcast receiving device 1 or a monitor 110 of a single display. Explained in the example. However, the image processing device according to the present invention is a processing unit that executes video signal processing of a multi-display (image display device) 100 in which a plurality of display units 6 are arranged in the vertical and horizontal directions as shown in FIG. You may apply to. In this case, the multi-display 100 is the image display device according to the present invention. Since the image processing apparatus according to the present invention is applied to a processing unit that executes video signal processing of the multi-display 100, for example, when playing an FHD video on the multi-display 100, the detail feeling of the video is high-quality. Can be executed.

[Example of software implementation]
The television broadcast receiver, the monitor or the multi-display control unit (especially the video signal processing unit) of the first to sixth embodiments may be realized by a logic circuit (hardware) formed in an integrated circuit (IC chip) or the like. Alternatively, it may be realized by software using a CPU (Central Processing Unit).

  In the latter case, the television broadcast receiver, the monitor or the multi-display includes a CPU for executing instructions of a program which is software for realizing each function, and a ROM in which the program and various data are recorded so as to be readable by the computer (or CPU). (Read Only Memory) or a storage device (these are referred to as “recording media”), a RAM (Random Access Memory) for expanding the program, and the like. And the objective of this invention is achieved when a computer (or CPU) reads the said program from the said recording medium and runs it. As the recording medium, a “non-temporary tangible medium” such as a tape, a disk, a card, a semiconductor memory, a programmable logic circuit, or the like can be used. The program may be supplied to the computer via an arbitrary transmission medium (such as a communication network or a broadcast wave) that can transmit the program. The present invention can also be realized in the form of a data signal embedded in a carrier wave in which the program is embodied by electronic transmission.

  The present invention is not limited to the above-described embodiments, and various modifications can be made. That is, embodiments obtained by combining technical means appropriately changed within the scope not departing from the gist of the present invention are also included in the technical scope of the present invention.

[Summary]
An image processing device (video signal processing unit 42) according to aspect 1 of the present invention is an image processing device including a detail processing unit that brings a fine feeling to a frame image constituting a video, and includes the detail processing unit (detail feeling). The improvement processing unit 13) includes a registration unit (positioning processing unit 17) that performs alignment between each pixel in the target frame image and its adjacent frame image, and an inter-frame correlation using the aligned frame image. A noise reduction unit (second noise reduction processing unit 18) that generates a noise reduced image from the target frame image by reducing an amplitude that can be regarded as a small noise, and a target pixel and its surrounding pixels for each pixel of the target frame image A maximum value / minimum value calculation unit (maximum value / minimum value calculation processing unit 19) for calculating a maximum value and a minimum value of pixel values in the first block including For each pixel of the target frame image, a high-frequency component generation unit (high-frequency component generation processing unit 20) that calculates a high-frequency component based on the pixel value of the target pixel and the maximum value and the minimum value calculated for the target pixel And a mixing unit (mixing processing unit 21) that generates an output frame image based on the target frame image, the noise-reduced image, and the high-frequency component.

  According to the above configuration, each pixel is aligned in the target frame image and its adjacent frame image, the amplitude that can be regarded as noise having a small inter-frame correlation is reduced, and a noise reduced image is generated from the target frame image. Then, the maximum value and the minimum value of the pixel value of the pixel in the first block including a plurality of pixels including the target pixel are obtained, and the high frequency component is calculated based on these values. Here, when a small size is selected as a block, a high-frequency component that is a source of fineness can be effectively calculated (generated) with a small size. Then, an output frame image is generated using the high-frequency component, the target frame image, and the noise reduction image.

  Therefore, according to the above configuration, it is possible to improve the detail feeling without enhancing the noise component. Note that it is difficult to determine whether it is a detail or noise by using only the information of the frame image alone. Therefore, it is an effective means to perform comparison between frame images as in the above configuration.

  Further, in the image processing device according to aspect 2 of the present invention, in the image processing device according to aspect 1, the noise reduction unit performs a pixel value of each pixel of the adjacent frame image with respect to the target frame image. The smaller the correlation, the smaller the weighting factor, and for the pixel value of each pixel of the target frame image, a predetermined weighting factor is set, and a weighted average is calculated using these to calculate noise from the target frame image. A reduced image may be generated.

  In the image processing device according to aspect 3 of the present invention, in the image processing device according to aspect 1 or 2, the high-frequency component generation unit includes: (a) a pixel value of the target pixel and the maximum calculated for the target pixel; If the absolute value of the difference from the value is larger than a value obtained by multiplying the absolute value of the difference between the pixel value of the target pixel and the minimum value calculated for the target pixel by a constant, the pixel value of the target pixel The value obtained by subtracting the maximum value calculated for the pixel as the high-frequency component of the pixel of interest is (b) the difference absolute value between the pixel value of the pixel of interest and the minimum value calculated for the pixel of interest is If the absolute value of the difference between the pixel value of the pixel of interest and the maximum value calculated for the pixel of interest is greater than a constant, the pixel value of the pixel of interest is calculated for the pixel of interest. The value obtained by subtracting the minimum value, as the high-frequency component of the target pixel may be calculated.

  In the image processing device according to aspect 4 of the present invention, in the image processing device according to any one of aspects 1 to 3, the mixing unit includes a pixel value of each pixel of the noise-reduced image and the high-frequency component. The output frame image may be generated by adding the enhancement amount based on the image and the adjustment amount based on the target frame image and the noise-reduced image.

  In the image processing device according to aspect 5 of the present invention, in the image processing device according to aspect 4, the mixing unit is configured to calculate a pixel value in a second block including the target pixel and the peripheral pixels in the target frame image. By multiplying the high frequency component by a first weighting factor determined for the difference between the maximum value and the minimum value, the enhancement amount is calculated, and the maximum value and the minimum value of the pixel values in the second block are calculated. The adjustment amount may be calculated by multiplying the difference between the pixel value of the target frame image and the pixel value of the noise-reduced image by a second weighting factor determined for the difference from the value. .

  As in the above configuration, the enhancement amount obtained by multiplying the high-frequency component by the first weighting factor determined for the difference between the maximum value and the minimum value of the pixel values in the second block, and the second block An adjustment amount obtained by multiplying the difference between the pixel value of the target frame image and the pixel value of the noise-reduced image by a second weighting factor determined for the difference between the maximum value and the minimum value of the pixel value of Is added to the pixel value of each pixel of the noise-reduced image to generate an output frame image. Therefore, it is possible to increase the weighting factor for the high-frequency component for an image region having a relatively narrow dynamic range, excluding an image region having an extremely small dynamic range where noise is conspicuous. At the same time, it is possible to suppress enhancement processing in an image region having a small dynamic range in which a small amplitude (noise) having a small correlation is conspicuous. Therefore, the effect of improving the detail feeling can be obtained without enhancing the noise component.

  Further, in the image processing device according to aspect 6 of the present invention, in the image processing device according to any one of aspects 1 to 5, the noise reduction unit is the previous frame image as the adjacent frame image. The result of processing the frame image by the noise reduction unit may be used.

  According to the above configuration, the noise reduction processing result in the frame image immediately before the target frame image can be reflected, so that the performance of the noise reduction processing can be improved. As described in the embodiment, a method using history information is effective.

  In the image processing device according to aspect 7 of the present invention, in the image processing device according to aspect 1, the maximum value / minimum value calculation unit further includes a pixel of interest for each pixel of the aligned adjacent frame image. And the maximum value and the minimum value of the pixel values in the first block including the surrounding pixels, and the high-frequency component generation unit further selects a pixel of the target pixel for each pixel of the aligned adjacent frame image A high-frequency component based on the value and the maximum value and the minimum value calculated for the pixel of interest, and each pixel of the adjacent frame image aligned with the high-frequency component of each pixel of the target frame image A new high-frequency component is calculated based on the high-frequency component, and the mixing unit is configured to output the output frame based on the target frame image, the noise reduction image, and the new high-frequency component. Over-time image may be generated.

  According to the above configuration, it is possible to suppress flicker caused by a difference in the amount of enhancement between frames. In addition, by using a small mask size, it is possible to effectively generate a high-frequency component without enhancing an unnecessary high-frequency component while reducing the thickness of the contour. Therefore, the feeling of detail can be improved without enhancing the noise component.

  In the image processing device according to aspect 8 of the present invention, in the image processing device according to aspect 7, the high-frequency component generation unit is configured to (a) focus on the target frame image and the aligned adjacent frame image. The difference absolute value between the pixel value of the pixel and the maximum value calculated for the target pixel is a value obtained by multiplying the absolute difference between the pixel value of the target pixel and the minimum value calculated for the target pixel by a constant. Is larger than the pixel value of the target pixel, a value obtained by subtracting the maximum value calculated for the target pixel as the first high-frequency component of the target pixel, and (b) the pixel value of the target pixel and the target pixel The difference absolute value calculated from the minimum value calculated for the pixel of interest is greater than the value obtained by multiplying the absolute value of the difference between the pixel value of the target pixel and the maximum value calculated for the target pixel by a constant. If so, a value obtained by subtracting the minimum value calculated for the pixel of interest from the pixel value of the pixel of interest is calculated as the first high-frequency component of the pixel of interest and calculated for each pixel of the adjacent frame image. For the first high-frequency component, a smaller weighting factor is obtained as the correlation with the target frame image is smaller. For the first high-frequency component calculated for each pixel of the target frame image, a predetermined weighting factor is used. And calculating a weighted average using these, the second high frequency component may be generated, and the mixing unit may use the second high frequency component as the new high frequency component.

  In the image processing device according to aspect 9 of the present invention, in the image processing device according to aspect 7 or 8, the mixing unit includes the target pixel and its surroundings in the target frame image and the aligned adjacent frame image. The second high-frequency component is multiplied by a first weighting factor determined for the maximum difference that is the maximum difference between the maximum and minimum pixel values in the second block including the pixel. The amount of enhancement is calculated, and the adjustment amount is calculated by multiplying the difference between the target frame image and the noise-reduced image by the second weighting factor determined for the maximum difference, and the noise The output frame image may be generated by adding the pixel value of each pixel of the reduced image, the enhancement amount, and the adjustment amount.

  According to the above configuration, it is possible to suppress flicker that occurs due to a change in the amount of enhancement between adjacent frames due to a difference in dynamic range between frames. Further, by using a small mask size, a high frequency component can be generated effectively.

  An image processing apparatus according to aspect 10 of the present invention is the image processing apparatus according to any one of aspects 1 to 9, wherein the image is displayed on the frame image output from the detail processing unit. A scaler processing unit that performs scaling processing according to the number of pixels of the unit, and a sharpness processing unit that performs contour enhancement processing on the frame image output from the scaler processing unit.

  According to the above configuration, it is possible to improve the feeling of detail before being damaged by the scaling process. Also, by performing the sharpness process after the scaling process, it is possible to improve the fineness while improving the sharpness without increasing the outline.

  An image display device according to aspect 11 of the present invention includes any one of the image processing devices according to aspects 1 to 10. Since the image processing apparatus according to any one of the above aspects is provided, the feeling of detail can be improved without enhancing the noise component. Therefore, high-quality and high-definition video can be displayed. Therefore, a high-performance and comfortable visual environment can be provided to the user.

  The image processing apparatus according to the present invention may be realized by a computer. In this case, a program for realizing the image processing apparatus by the computer by causing the computer to operate as the respective units, and the program are recorded. Such computer-readable recording media also fall within the scope of the present invention.

  The present invention can be used in an image processing apparatus or the like that processes video composed of a plurality of frames.

1 TV broadcast receiver (image display device)
4 Control section 6 Display section 8 Operation section 13, 13a, 13b, 13c Detail feeling improvement processing section (detail processing section)
17, 17a Positioning processing unit (positioning unit)
18, 18a Second noise reduction processing unit (noise reduction unit)
19, 19A, 19B Maximum value / minimum value calculation processing unit (maximum value / minimum value calculation unit)
19a First maximum value / minimum value calculation processing unit (maximum value / minimum value calculation unit)
19b, 19b 'second maximum value / minimum value calculation processing unit (maximum value / minimum value calculation unit)
19c Third maximum value / minimum value calculation processing unit (maximum value / minimum value calculation unit)
20, 20b High-frequency component generation processing unit (high-frequency component generation unit)
21, 21b Mixing processing unit (mixing unit)
42 Video signal processing unit (image processing device)
100 Multi-display (image display device)
110 Monitor (image display device)

Claims (13)

An image processing apparatus including a detail processing unit that brings a sense of fineness to a frame image constituting an image, wherein the detail processing unit includes:
An alignment unit that performs alignment between each pixel in the target frame image and its adjacent frame image;
A noise reduction unit that reduces an amplitude that can be regarded as noise with small inter-frame correlation using the aligned frame image, and generates a noise reduced image from the target frame image;
For each pixel of the target frame image, a maximum value / minimum value calculation unit for calculating the maximum value and the minimum value of the pixel value in the first block including the target pixel and its surrounding pixels;
For each pixel of the target frame image, a high frequency component generation unit that calculates a high frequency component based on the pixel value of the target pixel and the maximum value and the minimum value calculated for the target pixel;
An image processing apparatus comprising: a mixing unit that generates an output frame image based on the target frame image, the noise-reduced image, and the high-frequency component.   For the pixel value of each pixel of the adjacent frame image, the noise reduction unit applies a smaller weighting factor to the pixel value of each pixel of the target frame image, as the correlation with the target frame image is smaller. 2. The image processing apparatus according to claim 1, wherein a predetermined weighting factor is set, a weighted average is calculated using these, and a noise reduced image is generated from the target frame image. The high frequency component generator is
(A) The absolute difference value between the pixel value of the target pixel and the maximum value calculated for the target pixel is a constant difference absolute value between the pixel value of the target pixel and the minimum value calculated for the target pixel. Is larger than the value obtained by multiplying the pixel value of the target pixel by subtracting the maximum value calculated for the target pixel as the high frequency component of the target pixel.
(B) The difference absolute value between the pixel value of the target pixel and the minimum value calculated for the target pixel is a constant difference absolute value between the pixel value of the target pixel and the maximum value calculated for the target pixel. If the value is greater than the value obtained by multiplying the pixel of interest by subtracting the minimum value calculated for the pixel of interest from the pixel value of the pixel of interest as the high frequency component of the pixel of interest,
The image processing apparatus according to claim 1, wherein the image processing apparatus calculates the image processing apparatus.   The mixing unit adds the pixel value of each pixel of the noise reduced image, the enhancement amount based on the high frequency component, and the adjustment amount based on the target frame image and the noise reduced image, thereby adding the output. The image processing apparatus according to claim 1, wherein a frame image is generated. The mixing part is
Multiplying the high-frequency component by a first weighting factor determined for a difference between a maximum value and a minimum value of pixel values in the second block including the target pixel and its peripheral pixels in the target frame image. To calculate the above emphasis amount,
Multiplying the difference between the pixel value of the target frame image and the pixel value of the noise-reduced image by a second weighting factor determined for the difference between the maximum value and the minimum value of the pixel values in the second block The image processing apparatus according to claim 4, wherein the adjustment amount is calculated.   6. The noise reduction unit according to claim 1, wherein the noise reduction unit uses, as the adjacent frame image, a result of processing the frame image immediately before the target frame image by the noise reduction unit. An image processing apparatus according to 1. The maximum value / minimum value calculation unit further calculates a maximum value and a minimum value of pixel values in the first block including the target pixel and its surrounding pixels for each pixel of the aligned adjacent frame image. ,
The high frequency component generation unit further calculates a high frequency component for each pixel of the aligned adjacent frame image based on the pixel value of the target pixel and the maximum value and the minimum value calculated for the target pixel. And calculating a new high-frequency component based on the high-frequency component of each pixel of the target frame image and the high-frequency component of each pixel of the aligned adjacent frame image,
The image processing apparatus according to claim 1, wherein the mixing unit generates the output frame image based on the target frame image, the noise reduced image, and the new high frequency component. The high frequency component generator is
For the target frame image and the aligned adjacent frame image, (a) the absolute difference between the pixel value of the target pixel and the maximum value calculated for the target pixel is the pixel value of the target pixel and the If the absolute value of the difference from the minimum value calculated for the pixel of interest is greater than a constant, a value obtained by subtracting the maximum value calculated for the pixel of interest from the pixel value of the pixel of interest As the first high-frequency component of the pixel, (b) the absolute difference between the pixel value of the target pixel and the minimum value calculated for the target pixel is the maximum value calculated for the pixel value of the target pixel and the target pixel. A value obtained by subtracting the minimum value calculated for the target pixel from the pixel value of the target pixel if the absolute value of the difference from the value is greater than a constant multiplied by a constant. As the first high-frequency component, calculated,
For the first high-frequency component calculated for each pixel of the adjacent frame image, a smaller weight coefficient is assigned to the first high-frequency component calculated for each pixel of the target frame image as the correlation with the target frame image is smaller. For the above, a predetermined weighting factor is set, and a weighted average is calculated using these to generate a second high frequency component,
The image processing apparatus according to claim 7, wherein the mixing unit uses the second high-frequency component as the new high-frequency component. The mixing part is
The maximum difference that is the maximum difference between the maximum value and the minimum value of the pixel values in the second block including the target pixel and its surrounding pixels in the target frame image and the aligned adjacent frame image The amount of enhancement is calculated by multiplying the second high frequency component by the first weighting factor determined for
An adjustment amount is calculated by multiplying the difference between the target frame image and the noise-reduced image by a second weighting factor determined for the maximum difference,
The image processing apparatus according to claim 7 or 8, wherein the output frame image is generated by adding a pixel value of each pixel of the noise reduced image, the enhancement amount, and the adjustment amount. A scaler processing unit that performs a scaling process according to the number of pixels of the display unit that displays the video on the frame image output from the detail processing unit;
The image processing apparatus according to claim 1, further comprising: a sharpness processing unit that performs an edge enhancement process on the frame image output from the scaler processing unit.   An image display device comprising the image processing device according to claim 1.   A program for operating the image processing apparatus according to any one of claims 1 to 10, wherein the program causes a computer to function as each unit described above.   A computer-readable recording medium on which the program according to claim 12 is recorded.

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