Algorithm Research on Improving Halo Defects Based on Guided Filtering

In this paper, the improvement of guided filtering on halo defects in spatial color gamut mapping is proposed. The halo phenomenon is the main defect of the spatial color gamut mapping algorithm. This paper analyzes the principle and theoretical calculation method of guided filtering and proposes a new algorithm to improve the halo defect based on guided filtering. The mapping experiment of the new algorithm is carried out, and compared with the HPMinDE algorithm, the secondary algorithm in the paper. The comprehensive evaluation is carried out from three aspects of image color difference value, structural similarity, and algorithm running time. The results show that the new algorithm proposed in this paper has smaller color difference, larger structural similarity index and is closer to the original image, which verifies the feasibility and advantages of this algorithm. The research results of this paper have positive significance in the field of spatial color gamut mapping, and also have certain application value in the fields of edge detection, tone mapping, non-photorealistic rendering, and so on.