Recovery of Grayscale Image from Its Halftoned Version Using Smooth Window Function
Keywords:Convolution, cross correlation co-efficient, discrete wavelet transform, Floyd-Steinberg algorithm, process time
In a grayscale image of 256 levels, it is indistinguishable between intensity levels hence it is called continuous tone image. In a binary image the mark and space are
distinguishable but sharp change in intensity level makes the quality of the image very poor. The half tone image is also a binary image but varying the size of pixels and its density improves the quality of the image. The halftone image here can be considered as the truncated normalized version of continuous tone image. Based on this concept smoothing the transition of half tone image by convolutional operator with a smooth window function can recover the continuous tone image. Finally noise
grains are eliminated applying DWT (Discrete Wavelet Transform), gives the much closed perception of grayscale image. Although the similar concept is applied in blurring of a continuous tone image but in this paper similar concept is applied to half-tone operation to avoid the complexity of RI (Recursive Inverse) and RWI (Regularized Wiener Inversion) algorithm.
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