A color to gray conversion based on visual feature extraction of JND
Nowadays, in many applications, we need to convert images from color to gray scale and preserve both the visual appearance and feature discrimination. This paper presents a maximum entropy algorithm, a new color to gray conversion, based on the Just noticeable difference (JND) Unlike previous approaches, the proposed method extracts the visual feature edges in the image based on the characteristics of human eye recognition. And we propose an entropy based algorithm to choose the optimal line direction so that all the pixel color vectors in an image have the most spread out projections, thus increasing the grayscale image contrast. Then, we make use of histogram specification on all the edge pixels to further increase the image contrast. Experimental results demonstrate that the proposed method is superior to the current methods in terms of both image quality and information presentation.
2016 International Conference on Progress in Informatics and Computing (PIC)