Title: "Contrast Enhancement Based on Gaussian Mixture Modeling With Noise Adaptive Fuzzy Switching Median Filter"
         

Page(s): 9 - 15
Authors: Jayasilpa S, Kavitha N Nair

Abstract

Abstract—The proposed algorithm automatically enhances the contrast in an input image. The algorithm uses the Gaussian mixture model to model the image gray-level distribution. In a mixture distribution, its density function is just a convex combination (a linear combination in which all coefficients or weights sum to one) of other probability density functions. The Gaussian components with small variances are weighted with smaller values than the Gaussian components with larger variances By enhancing the contrast of an image in such a way might amplify noise if present and produce worse results. A noise adaptive fuzzy switching median filter is used for salt-and-pepper noise removal. It is able to suppress high-density of salt-and-pepper noise, at the same time preserving fine image details, edges and textures.

Keywords- Gaussian Mixture Model (GMM), Noise Adaptive Fuzzy Switching Median ( NAFSM), Bihistogram Equalization (BBHE), Minimum Mean Brightness Error Bi-Histogram Equalization (MMBEBHE). Recursive Mean Separate Histogram Equalization (RMSHE)