Detail enhancement decolorization algorithm based on rolling guided filtering

An important goal of color image gray-scale is to keep the edge details of the original color image as much as possible. In many cases, the degree of feature discrimination is maintained, but in some cases, edge details are still lost or blurred. Therefore, this paper first uses an improved non-linear global mapping grayscale method to grayscale the color image, and then proposes a grayscale image detail enhancement algorithm based on rolling guided filtering. The method in this paper is to enhance the edge details of the grayscale image by rolling guided filter processing on the basis of the grayscale image. In addition, the rolling-guided filter is a local linear model with better edge retention characteristics, which can overcome the defect that other filters are prone to gradient flips on the edges where the gray level of the image changes sharply, causing the image to appear “false edges”. The experimental results show that when the traditional method loses or blurs the detailed features, the method in this paper can maintain better detailed features.