JP2009118080A - Image signal processing apparatus, and image signal processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image signal processing apparatus and an image signal processing method which are capable of reducing the loss of a signal component while improving suppression of mosquito noise, block noise, etc. <P>SOLUTION: A control signal generation means 30 uses a contour detection signal from a contour detection filter 10 and a standard deviation from a means detecting variations 20 to calculate an image quality control value k and supplies a control signal including the image quality control value k to a first control part 60 and a second control part 70. The first control part 60 supplies a signal resulting from multiplying an output from a high band frequency extraction filter 50 by the image quality control value k of the control signal and adding an output signal from a smoothing filter 40 to the multiplication result, to the second control part 70. The second control part 70 adds a signal resulting from multiplying an input image signal by the image quality control value k and a signal resulting from multiplying the output signal from the first control part 60 by 1-k and outputs the addition result as an output signal of a noise reduction device 100. <P>COPYRIGHT: (C)2009,JPO&INPIT

Description

  The present invention relates to an image signal processing apparatus and an image signal processing method for reducing image noise caused by signal compression encoding / decoding of an image.

In recent years, digital broadcasting that replaces conventional analog broadcasting has been started. Since digital broadcasting displays images by digital processing, it has the following problems that are different from conventional analog broadcasting.
1. When compression is performed according to a compression method stipulated by MPEG2, mosquito noise is generated due to quantization errors of high frequency components that occur in relation to the compression rate.
2. When compression is performed according to the compression method stipulated by MPEG2, block noise is generated due to quantization error of the average luminance component that occurs in relation to the compression rate.

  The generation of these noises is due to a different cause from the noise generated in conventional analog broadcast receivers, and the generation conditions are also different. For this reason, these noises are generated also for (1) component signals, and (2) have the particularity that there is correlation and regularity with the signals.

  Here, the particularity of (1) will be described. In the conventional analog broadcasting, noise due to the broadcast format is generated only in the composite input signal and not in the RGB component input signal. However, in digital broadcasting, noise due to the broadcast format is generated even in RGB component signals.

  The special feature (2) is that in digital broadcasting, noise occurs near the contour of a signal, regular block boundaries occur, and the noise level at that time has signal level dependency. Means.

  On the other hand, as a conventional noise removal circuit, there is a cyclic noise reduction device using a frame memory (see, for example, Patent Document 1). An example of the configuration of this noise reduction device is shown in FIG. The noise reduction apparatus shown in FIG. 11 includes a multiplier 91 that multiplies a gain K, a delay circuit 92 that acquires an image of the previous frame, a multiplier 93 that multiplies a gain (1-K), and a multiplier. And an adder 94 for adding the output signals 91 and 93. Then, a signal obtained by adding the value obtained by multiplying the input signal by the gain K and the value obtained by multiplying the signal of the previous frame acquired by the delay circuit 92 by the gain (1-K) is output as an output signal. .

As a conventional noise removal circuit, there is a noise reduction device in which coring is applied to a sharpness circuit (see, for example, Patent Document 2). In this coring processing unit, a signal spread over a wide frequency band is cut as white noise at a fixed level (coring level). An example of the configuration of this noise reduction device is shown in FIG. The noise reduction device shown in FIG. 12 includes a high frequency filter 95 and a low frequency filter 96. Of the components of the high frequency filter 95 in the input signal, components below the coring level are removed, and gain adjustment is performed on the remaining components. Then, an output signal is generated by adding the signal that has passed through the low-frequency filter 96 of the input signal.
Japanese Patent Laid-Open No. 7-162807 (FIG. 3) Japanese Patent Laid-Open No. 10-200787 (first page)

  Conventionally, the mosquito noise generated in the digital broadcasting system depends on the magnitude of the frequency component of the signal outline, and the noise level changes. In addition, this mosquito noise occurs in both still images and moving images.

  On the other hand, block noise tends to appear when the average luminance component changes from block to block in a scene that changes relatively slowly. Even in a still image, when the compression rate is increased, the fixed block boundary appears clearly as noise. Furthermore, when the amount of motion such as a scene change changes drastically in a moving image, block noise becomes conspicuous.

  Here, in order to suppress the mosquito noise and the block noise, when the noise reduction device described in Patent Document 1 is used, the performance of removing random noise in a still image is high. However, it has no effect on noise with a fixed pattern.

Furthermore, when the above-described coring technique is used, in order to improve the degree of suppression, it is necessary to significantly increase the coring level from the characteristics of these noises.
In the noise reduction device described in Patent Document 2, since the coring level is an absolute value, signal components below the coring level are also lost. Furthermore, even if the input signal is the same, if the contrast (gain) changes depending on the system, the signal component lost due to coring also changes.

  The present invention has been made in view of the above problems, and provides an image signal processing device and an image signal processing method that can reduce loss of signal components while improving the degree of suppression of noise such as mosquito noise and block noise. There is.

  In order to solve the above problem, the invention according to claim 1 acquires an input image signal composed of a block in which element pixels are arranged two-dimensionally, and smoothes a high frequency component of the input image signal. Smoothing means for generating a smoothed signal, contour detecting means for detecting a contour component in the input image signal, dispersion amount detecting means for calculating a variation amount of element pixels in the block, and a center in the block An image obtained by adjusting the smoothing signal and the input image signal using the image quality control value, and a control signal generation unit that calculates an image quality control value based on the comparison between the contour component and the variation amount for the pixel. The gist of the invention is that it includes image quality adjusting means for generating an output signal.

  According to a second aspect of the present invention, in the image signal processing apparatus according to the first aspect, the control signal generating means sets the value of the output signal of the contour detecting means to YE, and the value of the output signal of the dispersion amount detecting means. Is the image quality control value using the image quality control value calculation formula displayed as image quality control value k = (YE * β1) / (σ * β2 + α), where σ is the constant and β1, β2, and α are constants. Is the gist.

  According to a third aspect of the present invention, in the image signal processing device according to the second aspect, the image quality adjustment unit generates the input image adjustment signal by multiplying the input image signal by the image quality control value. A multiplier, a second multiplier for generating a smoothed adjustment signal by multiplying a signal generated based on the smoothed signal by a weighted value using the image quality control value, and the input image adjustment The gist is provided with an adder for adding the signal and the smoothing adjustment signal to generate an image output signal.

According to a fourth aspect of the present invention, in the image signal processing device according to the third aspect, the high frequency component is extracted from the input image signal, and the high frequency component is multiplied by the image quality control value to correct the contour component. A first control unit including a contour correction signal generation unit that generates a signal and an addition unit that adds the smoothing signal and the contour component correction signal; and the image quality adjustment unit includes: In other words, the smoothing adjustment signal is generated by multiplying the above signal by a weighted value using the image quality control value.

  According to a fifth aspect of the present invention, in the image signal processing device according to the fourth aspect, the output signal of the first control unit and the smoothed signal are added by weighting using a weighting coefficient, and the added signal The image quality adjusting means multiplies the signal from the weight processing means by a value weighted using the image quality control value to generate a smoothed adjustment signal. The gist.

  According to a sixth aspect of the present invention, smoothing is performed for acquiring an input image signal composed of blocks in which element pixels are arranged two-dimensionally and generating a smoothed signal obtained by smoothing high frequency components of the input image signal. A contour detecting step for detecting a contour component in the input image signal; a dispersion amount detecting step for calculating a variation amount of the element pixel in the block; and the contour component and the variation for a central pixel in the block A control signal generation step of calculating an image quality control value based on a comparison with the amount; an image quality adjustment step of generating an image output signal obtained by adjusting the smoothed signal and the input image signal using the image quality control value; The main point is that

(Function)
According to the first or sixth aspect of the invention, the smoothed signal is generated by smoothing the high frequency component of the input image signal image signal. Further, the contour component in the input image signal is detected, the variation amount of the element pixel in the block is calculated, and the image quality control value is calculated based on the comparison between the contour component and the variation amount for the central pixel in the block. Using this image quality control value, an output signal obtained by adjusting the smoothed signal and the input image signal is generated. The generation amount of mosquito noise and block noise is specified by the relationship between the output signal of the contour detection means and the output signal of the dispersion amount detection means, and the smoothed signal and the input image signal are adjusted according to the generation amount and output. Output a signal. For this reason, the ratio of the smoothed signal can be automatically changed based on the image quality control value that changes according to the noise situation. Therefore, the degree of suppression of mosquito noise and block noise can be improved, and loss of signal components included in the input image signal can be reduced.

  According to the second aspect of the present invention, the image quality control value calculation formula assumes that the value of the output signal of the contour detection means is YE, the value of the output signal of the dispersion amount detection means is σ, and constants are β1, β2, and α. The image quality control value k = (YE * β1) / (σ * β2 + α). In this case, if the constants β1, β2, and α are selected according to the amount of change in mosquito noise or block noise to be removed, a noise suppression effect can be obtained more efficiently. Further, when the value σ of the output signal of the dispersion amount detection means is close to “0”, it is possible to suppress the image quality control value from fluctuating greatly due to a minute change in the value σ, and a stable image quality control signal Can be output.

  According to the third aspect of the present invention, the image quality adjusting means generates an input image adjustment signal by multiplying the input image signal by the image quality control value, and for the signal generated based on the smoothed signal. Then, the smoothed adjustment signal is generated by multiplying the weighted value using the image quality control value, and the output signal is generated by adding the input image adjustment signal and the smoothed adjustment signal. Thereby, adjustment of a smoothing signal and an input image signal is realizable based on an image quality control value.

According to the fourth aspect of the present invention, the high frequency component is extracted from the input image signal, the contour component is extracted by multiplying the high frequency component and the image quality control value, and the smoothed signal and the contour component are corrected. A first control unit for adding the signal is further provided, and a smoothing adjustment signal is generated based on the signal of the first control unit. Since the smoothed signal smoothes high frequency components, noise is removed, but contour components are also lost. Therefore, by adding the contour component correction signal based on the extracted high-frequency component to the smoothed signal, the smoothing adjustment signal is generated while changing the high-frequency component added according to the noise situation. Can do. Since a raw smoothed signal is generated using this smoothing adjustment signal, noise can be removed and a smoothed signal having a high frequency component can be used.

  According to the fifth aspect of the present invention, there is further provided weighting processing means for adding the output signal of the first control unit and the smoothed signal by weighting using a weighting coefficient and outputting the added signal. The image quality adjustment unit multiplies the signal from the weighting processing unit by a value weighted using the image quality control value to generate a smoothing adjustment signal. For this reason, the ratio of the priority between the resolution of the signal and the degree of noise suppression can be arbitrarily changed by arbitrarily setting the addition coefficient.

  According to the present invention, it is possible to reduce the loss of signal components while improving the degree of suppression of noise such as mosquito noise and block noise.

(First embodiment)
Hereinafter, an embodiment of a noise reduction device embodying the present invention will be described with reference to FIGS.

  As shown in FIG. 1, the noise reduction apparatus 100 according to the present embodiment includes a contour detection filter 10, a variation amount detection unit 20, a control signal generation unit 30, a smoothing filter 40, a high frequency extraction filter 50, and a first control unit. 60 and a second control unit 70 are provided. In this embodiment, the contour detection filter 10 functions as a contour detection unit, and the variation amount detection unit 20 functions as a dispersion amount detection unit. Further, the smoothing filter 40 functions as a smoothing unit, and the second control unit 70 functions as an image quality adjusting unit.

  A component video signal is input to the noise reduction device 100. Among the video signals, the block configuration unit converts the block of n rows and m columns (n and m are positive integers) into a contour detection filter 10, a variation amount detection means 20, a smoothing filter 40, and a high frequency extraction filter 50. And supplied to the second control unit 70. In the present embodiment, n = m = 3, and an input image signal of an element pixel configured by a 3 × 3 block is supplied to each functional unit.

[Configuration of Noise Reduction Device 100]
As shown in FIG. 2, the contour detection filter 10 detects an edge (contour) in a block from the difference in luminance between adjacent pixels. In this embodiment, the contour detection filter 10 uses a known Prewitt type filter. Specifically, the contour detection filter 10 includes a horizontal filter 11 in which each element in the first column, the second column, and the third column is “−1”, “0”, “1”, the first row, Each element in the second row and the third row includes a vertical filter 12 of “−1”, “0”, and “1”.

  In such a contour detection filter 10, when a signal of each pixel constituting the block passes through the horizontal filter 11, a difference in luminance between pixels adjacent in the horizontal direction is calculated. Further, when the signal of each pixel constituting the block passes through the vertical filter 12, the difference in luminance between pixels adjacent in the vertical direction is calculated.

Further, the contour detection filter 10 includes a calculation unit 13 for the contour detection signal YE. The calculation unit 13 generates a contour detection signal YE using a value obtained by passing through the horizontal filter 11 and the vertical filter 12 and the equation (1) in FIG. The contour detection filter 10 supplies the generated contour detection signal YE to the control signal generation means 30.

  The variation amount detection means 20 calculates the variation amount (standard deviation σ) of the pixels constituting the block. When there is no contour in the block, the amount of variation is usually small. Therefore, when the amount of variation is large, noise is generated. In addition, when there is a contour in the block, the amount of variation increases according to the amount of the contour.

  In the present embodiment, when calculating the standard deviation σ, the statistical average value S of the smoothing filter 40 is used. The variation amount detection means 20 calculates the variation amount (standard deviation σ) using the equation (2) in FIG. The variation amount detection unit 20 calculates the variation amount (standard deviation σ) from the signals of the pixels constituting the acquired block of the input image signal, and supplies the calculated standard deviation σ to the control signal generation unit 30.

  The control signal generator 30 outputs a control signal cont. The control signal cont includes an image quality control value k obtained by normalizing the contour detection signal YE with the standard deviation σ. Specifically, as shown in FIG. 4, the control signal generation unit 30 includes a comparison unit 31, an upper limit setting unit 32, and a control value calculation unit 33. The comparison unit 31 compares the contour detection signal YE acquired from the contour detection filter 10 with the standard deviation σ acquired from the variation amount detection unit 20. When the comparison unit 31 determines that the contour detection signal YE is greater than or equal to the standard deviation σ (in the case of “YES”), the upper limit setting unit 32 replaces the value of the contour detection signal YE with the same value as the standard deviation σ. .

  The control value calculation means 33 calculates the image quality control value k of the control signal cont by substituting the contour detection signal YE and the standard deviation σ into the expression (3) in FIG. The image quality control value k is “1” when the contour detection signal YE is equal to or greater than the standard deviation σ, and therefore has a size in the range of “0” to “1”. Further, the image quality control value k approaches “0” when the contour detection signal YE is smaller than the standard deviation σ even when the signal level fluctuates, and when the contour detection signal YE is larger than the standard deviation σ. Approaches “1”. The control signal generation unit 30 supplies the calculated image quality control value k to the first control unit 60 and the second control unit 70.

  On the other hand, the smoothing filter 40 is a filter that extracts a flat region from the input image signal. The smoothing filter 40 calculates a statistical average value S in the block, and uses a signal corresponding to the statistical average value S as an output signal. In the present embodiment, the median value of 9 pixels is used as the statistical average value S for calculating the variation amount (standard deviation σ). Specifically, as shown in FIG. 3, the smoothing filter 40 calculates the median value of the pixels (s1 to s9) constituting the 3 × 3 block acquired from the input image signal, and blocks the median value. The statistical average value S of By specifying the median value, it is possible to retain higher order spectral components as much as possible for relatively large edge components (ie, obvious signal components). The smoothing filter 40 supplies the calculated median value to the variation amount detection unit 20 and the first control unit 60.

  The high frequency extraction filter 50 shown in FIG. 1 extracts only the core frequency of the contour component from the components corresponding to the high frequency. The high-frequency extraction filter 50 supplies a predetermined range of frequency components from the input image signal to the first controller 60.

The first control unit 60 includes a multiplier 61 and an adder 62 as addition means. The multiplier 61 outputs a contour component correction signal obtained by multiplying the output signal from the high frequency extraction filter 50 by the image quality control value k. The high frequency extraction filter 50 and the multiplier 61 of the first control unit 60 function as a contour correction signal generation unit. The adder 62 adds the output signal from the smoothing filter 40 and the output signal from the multiplier 61. The output signal of the adder 62 is supplied from the first control unit 60 to the second control unit 70 as a signal generated based on the smoothed signal. Therefore, the first control unit 60 controls the signal strength of the contour component according to the image quality control value k, and superimposes it on the output from the smoothing filter 40.

  The second control unit 70 includes a first multiplier 71, a second multiplier 72, and an adder 73. The first multiplier 71 and the second multiplier 72 are supplied with the control signal cont generated by the control signal generation means 30 and acquire the image quality control value k. The first multiplier 71 outputs an input image adjustment signal obtained by multiplying the input image signal by “k”. The second multiplier 72 outputs a smoothing adjustment signal obtained by multiplying the output signal from the first control unit 60 by “1-k” (value weighted using the image quality control value). The adder 73 is supplied with the input image adjustment signal from the first multiplier 71 and the smoothing adjustment signal from the second multiplier 72, and outputs a signal obtained by adding them as an output signal of the second control unit 70. . The output signal of the second control unit 70 becomes the output signal (image output signal) of the noise reduction device 100.

[Operation of Noise Reduction Device 100]
Next, the processing operation of the noise reduction device 100 will be described.
When the video signal is input to the noise reduction device 100, the contour detection filter 10, the variation amount detection unit 20, the smoothing filter 40, the high-frequency extraction filter 50, and the second control unit 70 receive three lines of the video signal. Three rows of blocks are supplied sequentially.

  The contour detection filter 10 calculates the contour detection signal YE and supplies it to the control signal generation means 30. The variation amount detector 20 calculates the standard deviation σ and supplies it to the control signal generator 30. The control signal generation unit 30 calculates the image quality control value k using the contour detection signal YE and the standard deviation σ. Then, the control signal cont including the image quality control value k is supplied to the first control unit 60 and the second control unit 70.

  The smoothing filter 40 calculates the median value of the element pixels constituting the block, and supplies the median value to the variation amount detection means 20 and the adder 62 of the first control unit 60. In this case, mosquito noise and block noise are suppressed in the output signal of the smoothing filter 40, but the contour component is also lost. The high frequency extraction filter 50 acquires a predetermined range of frequency components in the block and supplies the frequency component to the multiplier 61 of the first control unit 60. The multiplier 61 of the first control unit 60 multiplies the output signal from the high frequency extraction filter 50 by the image quality control value k and supplies the result to the adder 62. The adder 62 adds the output signal from the multiplier 61 and the output signal from the smoothing filter 40 and supplies the result to the second control unit 70.

  The first multiplier 71 of the second control unit 70 multiplies the video signal by the image quality control value k and supplies it to the adder 73. The second multiplier 72 of the second control unit 70 calculates a signal obtained by multiplying the output signal from the first control unit 60 by “1-k” and supplies the signal to the adder 73. The adder 73 adds the output from the first multiplier 71 and the output from the second multiplier 72 and outputs the result as an output signal of the noise reduction device 100.

  When there is almost no outline (when the image quality control value k is close to “0”), the output signals of the multiplier 61 and the first multiplier 71 are almost “0”. In addition, the value of “1-k” of the second multiplier 72 becomes almost “1”, and the output of the smoothing filter 40 is preferentially output. In this case, since it is unnecessary to superimpose high frequency components, the median value is output with priority.

When the image quality control value k is close to “1”, the output signal of the first multiplier 71 is almost “1”, and the input image signal is output as it is.
Further, in the case of 0 <k <1, in the first control unit 60, the output from the high frequency extraction filter 50 has a magnitude corresponding to the image quality control value k and is added to the output from the smoothing filter. Is output. In the second control unit 70, a signal obtained by internally dividing the input image signal of the noise reduction device 100 and the output signal of the first control unit 60 according to the image quality control value k is output as an output signal of the noise reduction device 100. Is done.

  FIG. 6 shows a reference image displayed using the video signal input to the noise reduction device 100 as it is. FIG. 7 shows a reference image displayed using an image output signal output from the noise reduction device 100 to which this video signal is input. In the image of FIG. 7, it can be seen that mosquito noise and block noise are reduced compared to the image of FIG.

According to this embodiment, the following effects can be obtained.
(1) In the present embodiment, the control signal generation means 30 generates the control signal cont of the image quality control value k according to the ratio between the contour detection signal YE and the standard deviation σ, and the first control unit 60 and the second control To the unit 70. When the gain of the input image signal is changed so as to gradually decrease the contour detection signal YE and the standard deviation σ under the condition of σ = YE, the signal contrast approaches “0”, but the relative relationship between the signal pixels is increased. Since the relationship has not changed, “k = 1” is maintained. This means that if the relative level ratio between the pixels of the signal does not change, the size of the target contour component can be extracted and converted into a coefficient without depending on the absolute contrast.

  In the case of mosquito noise, in the table 500 shown in FIG. 5, it is a luminance alternating arrangement between adjacent pixels in the flat region of the signal in the vicinity of the contour, and is included in the (σ small, YE small) region. In the case of block noise, in the table 500 shown in FIG. 5, the luminance change pattern between several pixels continuous in the horizontal direction or the vertical direction and the left and right upper and lower pixels is included in the (σ small, YE large) region.

  The noise reduction device 100 outputs a signal obtained by adding an input image adjustment signal obtained by multiplying an input image signal by “k” and a smoothing adjustment signal based on an image quality control value k that changes according to a noise situation. And output as an output signal of the noise reduction device 100. Therefore, the ratio between the input image signal and the smoothing adjustment signal is automatically changed based on the image quality control value k that changes according to the noise situation. Therefore, the degree of suppression of mosquito noise and block noise can be improved, and loss of signal components included in the input image signal can be reduced.

  (2) In the present embodiment, the variation amount detection means 20 calculates the statistical average value S and uses a signal corresponding to this as the output signal. In the present embodiment, a signal is generated by adding the value obtained by multiplying the output signal of the high frequency extraction filter 50 by the image quality control value k and the statistical average value S of the smoothing filter 40. For this reason, the smoothing filter 40 and the variation amount detection means 20 perform the calculation using the same statistical average value S, so that the consistency can be improved.

  (3) In the present embodiment, the first control unit 60 adds the output signal from the smoothing filter 40 and the output signal from the high frequency extraction filter 50 according to the image quality control value k of the control signal cont. Output the signal. The smoothing filter 40 outputs an output signal that has no noise but has lost its contour. For this reason, by adding a value obtained by multiplying the high frequency component by the image quality control value to the smoothed signal, a signal generated by adding the high frequency component according to the noise condition is supplied to the second control unit 70. Then, an output corresponding to this signal can be performed.

(4) In the present embodiment, in the control signal generation means 30, when the comparison means 31 determines that the contour detection signal YE is equal to or greater than the standard deviation σ (in the case of “YES”), the upper limit setting means 32 The value of the detection signal YE is replaced with the same value as the standard deviation σ. The control value calculation means 33 of the control signal generation means 30 calculates the image quality control value k of the control signal cont by substituting the contour detection signal YE and the standard deviation σ into the expression (3) in FIG. For this reason, even when the contour detection signal YE takes a range larger than the standard deviation σ, the image quality control value k of the control signal cont can be set between “0” and “1”. The output signal from the apparatus 100 can be adjusted by the magnitude according to the input image signal.

  (5) In this embodiment, the contour detection filter 10 uses a known Previt filter. Block noise may occur as an edge extending in the horizontal direction or the vertical direction. The Previt method does not react when only the center row or the center column changes, and it is difficult to detect a specific pattern overlapping the features of mosquito noise and block noise as an outline. Therefore, it is difficult to detect noise having a high luminance difference between adjacent pixels as a contour, so that block noise and the contour can be more reliably identified.

(Second Embodiment)
Next, a second embodiment of the present invention will be described with reference to FIGS. In the present embodiment, a control signal generating unit 300 is used instead of the control signal generating unit 30 in the above embodiment. The control signal generation unit 300 differs from the control signal generation unit 30 in the method of calculating the image quality control value k. Moreover, in this embodiment, about the part similar to the said embodiment, the same code | symbol is used and the detailed description is abbreviate | omitted.

  The control signal generation unit 300 of this embodiment includes a contour component amount calculation unit 310, a comparison unit 320, an upper limit setting unit 330, and a control value calculation unit 340. The contour component amount calculating means 310 calculates the contour component amount GYE using the contour detection signal YE and the equation (4) in FIG. The comparison unit 320 compares the calculated contour component amount GYE with [σ * β2]. Here, β2 is a constant, and in this embodiment, “β2 = 1/8” is used.

  When the comparison unit 320 determines that the contour component amount GYE is equal to or larger than [σ * β2] (in the case of “YES”), the upper limit setting unit 330 sets the contour component amount GYE equal to [σ * β2]. Replace with a value.

  The control value calculation means 340 calculates the image quality control value k of the control signal cont by substituting the contour component amount GYE and the standard deviation σ into the equation (5) in FIG. Here, in the formula (5), β1 and α are constants, and in this embodiment, “β1 = 2” and “α = 1” are used.

  As shown in the table 600 of FIG. 9, when the contour component amount GYE is equal to or larger than [σ * β2], k≈1 when [σ * β2] is sufficiently larger than α, and “ 0.5 ". Further, when the contour component amount GYE is smaller than [σ * β2], k≈GYE / (σ * β2) is obtained when [σ * β2] is sufficiently larger than α, and when [σ * β2] is substantially equal to α, k is obtained. ≈ (GYE / (σ * β2)) / 2. Then, the control signal generation unit 30 supplies the calculated image quality control value k to the first control unit 60 and the second control unit 70.

  In this embodiment, since the control signal k <1 (α = 1 in the embodiment), as shown in FIG. 9, the maximum amount of the image quality control value k is determined by the magnitude of α. FIG. 9 shows the meaning of this control as a relationship between the signal classification and the image quality control value k of the control signal cont.

In this embodiment, in addition to the same effects as (1) to (5) in the first embodiment, the following effects can be obtained.
(6) In the present embodiment, the contour component amount calculating unit 310 of the control signal generating unit 30 calculates the contour component amount GYE using the contour detection signal YE and Equation (4). The control value calculation means 340 of the control signal generation means 30 calculates the image quality control value k of the control signal cont by substituting the contour component amount GYE and the standard deviation σ into the equation (5). Therefore, it is more efficient if “β1” in equation (4) and “β1” and “α” in equation (5) are selected according to the amount of mosquito noise or block noise to be removed. In addition, a noise suppression effect can be obtained.

  (7) In the present embodiment, the formula (5) using the formula obtained by adding α to the standard deviation σ is used. For this reason, when the standard deviation σ is close to “0”, it is possible to suppress the image quality control value k from fluctuating greatly due to a small change in the standard deviation σ, and to output a stable control signal cont. it can.

Moreover, you may change the said embodiment as follows.
In the above embodiment, the output signal of the first control unit 60 is supplied to the second control unit 70 as it is. Instead, as shown in FIG. 10, a noise reduction device 200 in which a weighting unit 80 is provided between the first control unit 60 and the second control unit 70 may be used. The weighting unit 80 functions as a weighting processing unit and is supplied with the output signal of the first control unit 60 and the output signal of the smoothing filter 40. The weighting unit 80 adds weights according to the addition coefficient between the output signal of the first control unit 60 and the output signal of the smoothing filter 40. By setting this addition coefficient, it is possible to arbitrarily change the priority ratio between the resolution of the signal and the degree of noise suppression.

  In the above embodiment, the smoothing filter 40 is used. However, the present invention is not limited to this as long as only a flat region of a signal having no mosquito noise or block noise can be extracted. For example, it is possible to employ a simple low-pass filter with a low cutoff. In the present embodiment, the median value of 9 pixels is used as the statistical average value S for calculating the standard deviation. However, the statistical average value S may be obtained by a simple method. For example, among the pixels constituting the 3 × 3 block in FIG. 3, the median value of five pixels (pixels s1, s3, s5, s7, s9 of the input image signal in FIG. 3) and the remaining four pixels ( A half value of the sum of the average values of s2, s4, s6, and s8) may be used as the statistical average value S.

  In the above embodiment, the variation amount detection means 20 is calculated using the output of the smoothing filter 40. Not limited to this, the variation amount detecting means 20 may use a simple average of nine pixels as the average value of all the pixels of the block.

  In the above embodiment, the control signal generation unit 30 calculates the image quality control value k of the control signal cont using the standard deviation σ calculated by the variation amount detection unit 20. Not limited to this, the control signal generating means 30 is not limited to the standard deviation σ, and may be any other value as long as the value indicates the amount of variation. For example, the value k of the control signal cont may be calculated using a variance that is a square value of the standard deviation σ.

The block diagram explaining the structure of the noise reduction apparatus of 1st Embodiment. The processing block diagram for demonstrating the structure of an outline detection filter. The processing block diagram explaining the structure of a variation | change_quantity detection means. The processing block diagram explaining the structure of a control signal production | generation means. Explanatory drawing for demonstrating the signal according to the magnitude | size of a contour detection signal and a standard deviation. Explanatory drawing explaining the image displayed based on the input image signal. Explanatory drawing explaining the image displayed based on the image output signal. The processing block diagram explaining the structure of the control signal production | generation means in 2nd Embodiment. Explanatory drawing for demonstrating the signal according to the magnitude | size of a contour detection signal and a standard deviation. The block diagram explaining the structure of the noise reduction apparatus in the example of a change. Explanatory drawing explaining the structure of the noise reduction apparatus in a prior art. Explanatory drawing explaining the structure of the noise reduction apparatus in a prior art.

Explanation of symbols

  k ... image quality control value, 10 ... contour detection filter as contour detection means, 20 ... variation amount detection means as dispersion amount detection means, 30, 300 ... control signal generation means, 31, 320 ... comparison means, 32, 330 ... Upper limit setting means, 33, 340... Control value calculation means, 40... Smoothing filter as smoothing means, 50... High-frequency extraction filter constituting contour correction signal generation means, 60. Multiplier constituting correction signal generating means, 62... Adder, 70... Second controller as image quality adjusting means, 71... First multiplier, 72. Weighting means as means, 100, 200... Noise reduction apparatus as image signal processing device, 310... Contour component amount calculating means.

Claims (6)

Smoothing means for acquiring an input image signal composed of blocks in which element pixels are arranged two-dimensionally and generating a smoothed signal obtained by smoothing a high-frequency component of the input image signal;
Contour detecting means for detecting a contour component in the input image signal;
A dispersion amount detecting means for calculating a variation amount of the element pixels in the block;
Control signal generating means for calculating an image quality control value based on a comparison between the contour component and the variation amount for the central pixel in the block;
An image signal processing apparatus comprising: an image quality adjusting unit that generates an image output signal obtained by adjusting the smoothed signal and the input image signal using the image quality control value. The control signal generating means
When the value of the output signal of the contour detection means is YE, the value of the output signal of the dispersion amount detection means is σ, and the constants are β1, β2, and α,
Image quality control value k = (YE * β1) / (σ * β2 + α)
The image signal processing apparatus according to claim 1, wherein the image quality control value is calculated using an image quality control value calculation formula displayed in step 1. The image quality adjusting means is
A first multiplier for multiplying an input image signal by the image quality control value to generate an input image adjustment signal;
A second multiplier that generates a smoothed adjustment signal by multiplying a signal generated based on the smoothed signal by a value weighted using the image quality control value;
The image signal processing apparatus according to claim 2, further comprising an adder that adds the input image adjustment signal and the smoothing adjustment signal to generate an image output signal. A contour correction signal generating means for extracting a high frequency component from the input image signal and multiplying the high frequency component by the image quality control value to generate a contour component correction signal;
A first control unit having addition means for adding the smoothed signal and the contour component correction signal;
The said image quality adjustment means produces | generates a smoothing adjustment signal by multiplying the value weighted using the said image quality control value with respect to the signal from the said 1st control part. Image signal processing device. A weight processing means for adding the output signal of the first control unit and the smoothed signal by weighting using a weighting coefficient and outputting the added signal;
5. The image according to claim 4, wherein the image quality adjustment unit generates a smoothing adjustment signal by multiplying a signal from the weighting processing unit by a value weighted using the image quality control value. Signal processing device. A smoothing step of acquiring an input image signal composed of blocks in which element pixels are arranged two-dimensionally and generating a smoothed signal obtained by smoothing a high-frequency component of the input image signal;
A contour detection step of detecting a contour component in the input image signal;
A dispersion amount detection step of calculating a variation amount of element pixels in the block;
A control signal generation step for calculating an image quality control value based on a comparison between the contour component and the variation amount for a central pixel in the block;
An image signal processing method comprising: an image quality adjustment step of generating an image output signal obtained by adjusting the smoothed signal and the input image signal using the image quality control value.