Абстрактный

An Efficient Contrast Enhancement Based On Image Equalization with Improved Threshold Median Filter

Nia Achu Issac, Anjaly Viswan

In this paper, a highly efficient contrast enhancement algorithm using Gaussian mixture modeling (GMM) is proposed for modeling the image gray level distribution. It gives better results compared to the existing algorithms .There are numerous enhancement techniques for contrast enhancement of which histogram equalization is mainly preferred due to its simplicity and effectiveness. The main limitations of this technique includes over enhancement and raised noise level. Hence this paper incorporates an enhancement criterion based on image equalization with improved threshold median filter which aims at enhancing the contrast along with suppression of impulse noise and preservation of edges .The proposed algorithm is adaptive and is free of parameter setting for a given dynamic range of soma in usa the enhanced image. It contributes effective enhancement and is applicable to both gray scale and color images.