Enhancement of the Quality of Images Based on Multiple Threshold Segmentation and Adaptive Gamma Correction

The quality of images often is affected adversely by illumination and contrast,leading to the need for illumination compensation in image enhancement. The main objective of this paper is to describe how to correct the local contrast in different area of the image so that the invisible features in the dark and bright areas are brought out and made visible to the human eye. Considering the fact that illumination and gamma variation are usually uneven and nonlinear. In this paper, we propose an image segmentation algorithm with multiple thresholds based on the Otsu algorithm for partitioning the image into multiple related areas. Also, a selfadaptive Gamma correction algorithm is introduced based on the best average gray gradient (AGG) criterion in order to obtain the best image quality. The experimental results show that the proposed method has better performance than the conventional algorithms.