The Analytic of Image Processing Smoothing Spaces Using Wavelet

Abstract

Abstract Image analysis took wide areas in many fields, including medicine, physics, and other areas where you need a tool to deal with it smoothly and softly without losing the original image information. Using an image of a sample of a physical atom that was analyzed and highlighting the compression and raising the noise, histogram and statistics the image statistics where the best results were recorded when using a specific threshold i.e. when pressing the methods were used the first has the threshold methods is Balance sparsity-norm, Remove near 0 and Bal-sparsity-norm(sqrt). As for the methods of raising the noise are fixed form thresholding method with soft threshold, penalize high with hard threshold, penalize medium with hard threshold, penalize low with hard threshold, Bal sparsity norm (sqrt) with soft threshold, where image parameters were divided into approximation coefficients and details coefficients. Through the analysis, a suitable threshold value was obtained, which helps to restore energy that leads to the fact that the compressed necessity did not lose much of its original information, which proves the new wavelets in the field of physical and medical imaging.