Contrast Enhancement Using Various Statistical Operations and Neighborhood Processing

Abstract

ABSTRACT

On the search for efficient face recognition algorithm subject to multiple environmental constraints

“…Generally, this leads to brightness redistribution such that all values are equally likely. According to [26] , histogram equalization has the advantage of being simple as well as producing image outputs with maximum entropy. However, [27] have suggested that histogram equalization is unable to improve all parts of the face image, stating that when the original image has irregular illumination, some details of the resulting image will still be too bright or dark.…”

Type2 Fuzzy Soft Computing Technique for Image Enhancement

“…This method has proven better for enhancing and it uses less processing time to enhance the image. In [15], based on novel algorithm with statistical operations and with neighbourhood computation, the image enhancement has been performed.This algorithm is good for preventing from side effects and it preserves the consistency and brightness of the image. In [16], Contrast Limited Adaptive Histogram Equalization (CLAHE) method for image enhancement and class 3 fuzzy C means clustering method for image segmenting.…”