JP2010263539A5

JP2010263539A5 -

Info

Publication number: JP2010263539A5
Application number: JP2009114356A
Authority: JP
Filing date: 2009-05-11
Publication date: 2012-05-31
Anticipated expiration: 2029-05-11

Description

また、条件式（４）は、注目するブロックの画素の差分（復元画像データの４つの画素ａ₀〜ｄ₀から求められる３つの差分ａ〜ｃ）の標準偏差σ²が所定の閾値σ_Hよりも小さく、且つ、その平均値ａｖに所定の閾値（倍率）ｓｃａｌｅ_Hを乗じた値よりも、境界における差分ｄの値の大きさ（境界を挟む画素の輝度変化の絶対値）が大きい場合を示している。すなわち、この条件式（４）は注目するブロックでの画素の変化が小さく、且つ、ブロックの境界における画素の輝度の変化量が急激に増加している場合（パターン３または４の場合）を示している。 Conditional expression (4) indicates that the standard deviation σ ² of the pixel difference of the block of interest (three differences a to c obtained from the four pixels a _{0 to} d ₀ of the restored image data) is a predetermined threshold σ _H. And the magnitude of the difference d at the boundary (the absolute value of the luminance change of the pixels across the boundary) is larger than the value obtained by multiplying the average value av by a predetermined threshold value (magnification) scale _H. Is shown. That is, this conditional expression (4) shows the case where the change in the pixel in the block of interest is small and the amount of change in the luminance of the pixel at the block boundary increases rapidly (in the case of pattern 3 or 4 ). ing.

Claims

An image quality evaluation method for evaluating the quality of image data processed by being divided into blocks composed of a plurality of pixels,
From the correlation of the values of at least three pixels among the pixels arranged in the horizontal direction or the vertical direction, and the difference in the values of the pixels sandwiching the block boundary among the pixels arranged in the horizontal direction or the vertical direction, the block An image quality evaluation method for detecting block distortion occurring at the boundary of the image.

In the image data, horizontal difference image data composed of differences calculated from the same direction in the order in which the pixels are arranged in the order in which the pixels are arranged in the horizontal direction, and pixels adjacent to the pixels arranged in the vertical direction. Generating vertical difference image data consisting of differences calculated from the same direction in the order in which the pixels are lined up,
From the difference image data in the horizontal direction and the difference image data in the vertical direction, the correlation of at least three values of the differences between the values of the pixels arranged in the horizontal direction or the difference between the values of the pixels arranged in the vertical direction. The block distortion generated at the boundary of the block is calculated from the correlation between at least three values, and the difference between the values of the pixels sandwiching the block boundary among the pixels arranged in the horizontal direction or the vertical direction. And detecting the image quality evaluation method according to claim 1 .

Detecting the block distortion comprises:
A standard deviation and an average value of the differences of the values of the pixels included in the block are calculated for each pixel arranged in the horizontal direction or the vertical direction and for each block, and the standard deviation is smaller than a predetermined threshold value. And the block distortion is detected when the condition that the difference between the values of the pixels sandwiching the boundary between the block and the adjacent block is larger than a value obtained by multiplying the average value by a predetermined magnification. The image quality evaluation method according to claim 2, which is configured as follows.

The step of detecting the block distortion further includes the above condition.
The positive and negative of the difference between each of the pixels sandwiching the boundary and the adjacent pixel are the same, and the positive or negative of the difference of the pixel value sandwiching the boundary is opposite to the positive or negative of the difference with the adjacent pixel The image quality evaluation method according to claim 3, configured to detect the block distortion when a certain condition is satisfied.

Detecting the block distortion comprises:
For each of the pixels arranged in the horizontal direction or the vertical direction, and for each block, the standard deviation and the average value of the differences of the values of the pixels included in the block, and the block included in the block adjacent to the block Calculating a standard deviation of the differences of pixel values, wherein each of the standard deviations is smaller than a predetermined threshold, and the magnitude of the difference of pixel values sandwiching a boundary between the block and an adjacent block is the average The image quality evaluation method according to claim 2, wherein the block distortion is detected when a condition that the value is larger than a value obtained by multiplying the value by a predetermined magnification is satisfied.

The step of detecting the block distortion further includes:
Regarding the block distortion detected for pixels arranged in the horizontal direction, only the detected block distortion that is continuous for a predetermined pixel or more in the vertical direction is used as the final block distortion.
Regarding the block distortion detected for pixels arranged in the vertical direction, only the detected block distortion that continues for a predetermined pixel or more in the horizontal direction is set as the final block distortion. The image quality evaluation method according to any one of claims 3 to 5.

7. The method according to claim 1, further comprising a step of calculating a block distortion amount by calculating a ratio of the total number of pixels included in the image data or a total number of the block distortions to the number of pixels constituting the block boundary. The image quality evaluation method according to one item.

The image quality evaluation method according to claim 1, wherein the image data is image data restored from an image compressed by a JPEG method or an MPEG method.

The program for making a computer perform the image quality evaluation method as described in any one of Claims 1-8.

An image quality evaluation apparatus for evaluating the quality of image data processed by being divided into blocks each composed of a plurality of pixels,
In the image data, horizontal difference image data composed of differences calculated from the same direction in the order in which the pixels are arranged in the order in which the pixels are arranged in the horizontal direction, and pixels adjacent to the pixels arranged in the vertical direction. A difference image generation unit that generates difference image data in the vertical direction consisting of differences calculated from the same direction in the order in which the pixels are arranged;
From the difference image data in the horizontal direction and the difference image data in the vertical direction, a correlation between at least three values of the differences between the pixel values arranged in the horizontal direction or the vertical direction is calculated, and the correlation and the horizontal direction or An image quality evaluation apparatus comprising: a block distortion detection unit configured to detect a block distortion generated at the block boundary from the difference between values of pixels sandwiching the block boundary among the pixels arranged in the vertical direction.

The block distortion detector
A standard deviation and an average value of the differences of the values of the pixels included in the block are calculated for each pixel arranged in the horizontal direction or the vertical direction and for each block, and the standard deviation is smaller than a predetermined threshold value. And the block distortion is detected when the condition that the difference between the values of the pixels sandwiching the boundary between the block and the adjacent block is larger than a value obtained by multiplying the average value by a predetermined magnification. The image quality evaluation apparatus according to claim 10, which is configured as follows.

In addition to the above conditions, the block distortion detector further includes:
The positive and negative of the difference between each of the pixels sandwiching the boundary and the adjacent pixel are the same, and the positive or negative of the difference of the pixel value sandwiching the boundary is opposite to the positive or negative of the difference with the adjacent pixel The image quality evaluation apparatus according to claim 11, configured to detect the block distortion when a certain condition is satisfied.

The block distortion detector
For each of the pixels arranged in the horizontal direction or the vertical direction, and for each block, the standard deviation and the average value of the differences of the values of the pixels included in the block, and the block included in the block adjacent to the block Calculating a standard deviation of the differences of pixel values, wherein each of the standard deviations is smaller than a predetermined threshold, and the magnitude of the difference of pixel values sandwiching a boundary between the block and an adjacent block is the average The image quality evaluation apparatus according to claim 10, wherein the block distortion is detected when a condition that a value is larger than a value obtained by multiplying a predetermined magnification is satisfied.

The block distortion detector further includes:
Regarding the block distortion detected for pixels arranged in the horizontal direction, only the detected block distortion that is continuous for a predetermined pixel or more in the vertical direction is used as the final block distortion.
Regarding the block distortion detected for pixels arranged in the vertical direction, only the detected block distortion that continues for a predetermined pixel or more in the horizontal direction is set as the final block distortion. The image quality evaluation apparatus according to claim 11.

The block distortion amount detection unit further calculates a block distortion amount by calculating a ratio of the total number of the block distortions to the total number of pixels included in the image data or the number of pixels constituting the block boundary. The image quality evaluation apparatus as described in any one of -14.

The image quality evaluation apparatus according to any one of claims 10 to 15, further comprising a data reading unit that generates the image data by reading and restoring data compressed by the JPEG method or the MPEG method.

The image quality evaluation apparatus according to claim 10, further comprising a display unit that displays the image data and the detection result of the block distortion so as to overlap each other.