Research on blur discrimination thresholds of three-Channel for color image

Abstract

On the basis of modern theory of color vision, the blur discrimination threshold of color image with three channels (luminance, red-green and the yellow-blue channel) in the opponent color space (DKL space) is studied through visual experiments in this paper. The visual evaluation experiment is designed by the psychophysical method based on Quest algorithm. Finding the blur discrimination threshold of color image according to the DKL space is of great significance for helping us understand color perception of image. It also has a wide range of applications in areas such as color image compression during color image transmission. Two (flowers and artificial object) typical images in the McGill standard color image database were chosen as the experimental images. After converting the color space of the image from RGB to DKL space, Gaussian low-pass filtering is used to establish the fuzzy image database. Quest algorithm which is a psychological physical method is used to design the visual evaluation experiment. Eleven volunteers with normal color vision were invited to participate in the visual evaluation experiment for each of the three channels of the two images. Our main conclusions are: (1) Human eyes are more sensitive to luminance information than color information. (2) The larger the contrast of the image and the smaller the uniformity of the image, the more sensitive the human eye is to changes in image blur.