Image Contrast Enhancement Algorithm Based On Human Visual Perception

In the modern society, the image carries a lot of information. Known, an image in the generation, transmission, receiving and processing may affect the quality of the image, which affect the readability and accuracy of the image. In the actual image applications, we found there are some useful information is masked, then we need to enhance image contrast, make its useful information to be enhanced, so the image contrast enhancement is very commonly used in digital image processing technology is particularly important.This article is aiming at these problems, according to the characteristics of the image or existing problems, combining with human visual perception characteristics(HVS)- minimum parallax(JND), set up a kind of improved algorithms of image of certain characteristics, aims to improve the visual effect or facilitate people or machines on the analysis of image understanding, for the computer of a basis for subsequent processing. In this paper, the main content as follows:1. First of all, describes in detail the human eye vision features, including the resolving power of the human eye to gray scale, the structure of the human eye to image and contrast sensitivity and the human eye is the smallest parallax(JND), which leads to the weber- fee cena’s law, which stimulate the variation of the human eye can feel difference threshold with the actual strength of the stimulus proportional relation, which provides the theoretical foundation for further research.2.Then, the paper introduces the traditional image contrast enhancement techniques and algorithms, through the use of Matlab software, the contrast of image enhancement, in the final analysis the quality of the image enhancement before and after, the eyes of its performance is superior to the adaptive enhancement technique.3. In addition, a large number of experiments on the C HOU model test, the CHOU model is improved and established in this paper, the JND model, finally achieved in Matlab. By comparing with the traditional image contrast enhancement technology, results show that the adaptive algorithm of human eyes processing of image quality is better.4. Finally, the system discussed the characteristics and limitations of the mainstream image contrast enhancement algorithm, and points out the image contrast enhancement technology research and development direction in the future.