Improvement of the Algorithm for Nonlinear Adaptive Image Contrast Enhancement Based on the Theory of Fuzzy Sets

Currently, primary image processing is used to improve recognition results. In this paper, improvements have been performed using normalization and phasing operations to increase image contrast. A normalized histogram has been also built. Mathematical expectations have been built for normalized and fuzzy image contrast enhancements. Shannon's entropy has been represented as fuzzy. Results of image sharpening have been presented and advantages over other algorithms have been indicated in the paper.