Curvature-Guided Color Image Restoration by Saturation-Value Total Variation

• Published in: Journal of mathematical imaging and vision Vol. 67; no. 1
• Main Authors: Wang, Wei, Wang, Jingjie, Ng, Michael K.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.01.2025; Springer Nature B.V
• Subjects: Algorithms; Applications of Mathematics; Color imagery; Computer Science; Curvature; Image Processing and Computer Vision; Image restoration; Mathematical Methods in Physics; Saturation (color); Signal,Image and Speech Processing; 68U10; 90C25; Saturation; Color image restoration; Value; Total variation; 65K10; 65J22; Curvature
• ISSN: 0924-9907; 1573-7683
• DOI: 10.1007/s10851-024-01218-6

In this paper, we propose a novel curvature-guided saturation-value total variation model for color image restoration. Specifically, we incorporate the curvature prior into the traditional variational model to guide the evolution in the direction that maintains the curvature information. Theoretically, we investigate the properties of the proposed model and give a detailed discussion based on the mathematical foundation about the existence of the solution. Numerically, we formulate an effective and efficient algorithm to solve the proposed minimization problem based on the framework of alternating direction method of multipliers. Numerical examples are presented to demonstrate that the performance of the proposed model is better than that of other testing methods for several testing color images.