Snow noise removing algorithm free of reference detection
A snowflake noise and algorithm technology, applied in the field of image processing, can solve the problem of time-consuming and labor-intensive subjective methods
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[0030] Such as figure 1 As shown, in order to detect and eliminate snowflake noise, the present invention first classifies the pixels with adjacent positions and similar gray levels (colors) into one block, and judges the noise points by judging the size of the block area, and outputs the original value of the non-noise points, and takes The adaptive mean of the signal points replaces the snowflake noise points, and compares the filtering result with the original image grayscale deviation to detect the snowflake noise. by figure 2 For example, for an image containing noise, apply a no-reference snowflake noise detection and elimination algorithm, which includes steps:
[0031] 5. Input the image f, and divide the image into sub-blocks;
[0032] 6. Form a noise block candidate set by screening sub-blocks;
[0033] 7. Adaptive filtering is adopted for each block in the noise block candidate set to generate an estimated image of a clear image;
[0034] 8. Determine whether t...
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