关键词: 人眼视觉, 灰度感知, 直方图均衡化, 临界可见偏差, 图像增强

Abstract: The traditional histogram equalization algorithm is doing histogram equalization processing on the image gray domain, rather than the human vision perceived brightness domain, leading local image may be too bright or too dark. Some scholars have proposed histogram equalization improvement algorithms in the human eye perceived brightness field. However, due to the inaccurate use of the human gray-scale perception model, the test results have not been significantly improved. Based on this, a modeling method of gray eye model is proposed. Firstly, the just noticeable difference curve of the human visual system is obtained by the experimental test method. Secondly, the sensitivity curve of the human eye to the same gray scale difference in different gray backgrounds is obtained. Thirdly, gray-scale human perception model is obtained through integrating and normalizing method based on previous step’s result. Finally, it reimplements the improved histogram equalization algorithm according to the above human gray-scale perception model. The comparing experiments show that the proposed algorithm is significantly improved than the traditional histogram equalization, and has many advantages including no adjusting parameters, remarkable enhancement effect, strong adaptability compared with CLAHE, BBHE and HMF.

Key words: human vision, gray-scale perception, Histogram Equalization（HE）, Just Noticeable Difference（JND）, image enhancement