UNSHARP MASKING USING CENTER WEIGHTED LOCAL VARIANCE FOR IMAGE SHARPENING AND NOISE SUPPRESSION

摘要

a so-called weighted local variance in the vicinity of a central image pixel determines the amplification factor by multiplying the difference between the image pixel and its counterpart in dark before it is combined with the original image.the amplification factor is determined for each pixel in the image, and varies from a minimum value of about - 1 where the headquarters is located in a weighted variance, minimum value, maximum value up to a given station when the weighted variance reaches a value. mm.the so-called weighted variance is calculated by convolution of the local neighborhood of each image pixel with a central core having a maximum weight value at pixel level. the so-called weighted variance is the difference between the weighted average of the square of the local neighbourhood of the central pixels of image and the square of the weighted average.we can obtain the image sharpness and the noise suppression in the image, allowing the amplification factor to vary between a fraction of a unit and the unit beyond the station as the weighted variance varies from a low value to a (consistent) e value (with picture).