Fuzzy dissimilarity contextual intensity transformation with gamma correction for color image enhancement

Abstract

The color image enhancement algorithm proposed here yields an improvement of the image data that suppresses undesired distortions or enhances some image features and convert an image to a format better suited to machine processing. The proposed Fuzzy Dissimilarity Contextual Intensity Transformation with Gamma Correction (FDCIT-GC) consists of following stages. At first, Fuzzy Dissimilarity Histogram (FDH) is constructed from the input image. It provides the mean dissimilarity value of each intensity level present in the input image. FDH is followed by clipping in order to restricts the over enhancement rate. In order to achieve better display fidelity rendition quality, Gamma Correction (GC) is applied. To restore the natural characteristics of the image, Contextual Intensity Transformation (CIT) is applied at next to get final enhanced images. Various color images from different database are experimented and the performance of the proposed FDCIT-GC algorithm is compared with several existing methods both subjectively and objectively. Test results demonstrate that the proposed algorithm achieves better outputs than other existing techniques.