Anti-sharpening masking and NSCT algorithm based mine image enhancing method
An anti-sharpening mask and image enhancement technology, applied in image enhancement, image data processing, calculation, etc., can solve the problems of noise sensitivity, high frequency part enhancement, overshoot, etc., to improve low illumination and suppress noise enhancement , the effect of avoided losses
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[0031] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0032] 1. Judging image details
[0033] (1) Calculate the local variance v(i, j) of each pixel, that is, a (2n+1)×(2n+1) window, f(i, j) is the gray value of the pixel in the center of the window, and the pixel The local variance of (i, j) is:
[0034]
[0035] Among them, f(k, l) is the gray value at the pixel point (k, l), Indicates the local mean of the pixel point (i, j), and n indicates an integer.
[0036] local mean of pixels for:
[0037] v(i, j) represents the level of detail of the pixel point (i, j).
[0038] (2) Set two thresholds T1 and T2, and T1
[0039] (3) According to the size of v(i, j), the image is divided into three detail areas: low, medium and high, namely: if v(i, j)1 It is a low-detail area; if T 1 2 It is the medium detail area; if v(i, j)>T 2 is a high detail area.
[0040] 2. Weighted instead of median filtering...
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