A Hue-Preserving Color Image Restoration Model Using Saturation-Value Total Variation

In this paper, we propose and develop a novel hue-preserving color image restoration model. In the proposed model, saturation-value total variation is used as the regularization term. In order to reduce hue loss during regularization, the huepreserving technique is incorporated into the proposed energy functional. We then rewrite the proposed model equivalently into a three-block separable convex version and apply an alternating direction method of multipliers based algorithm to solve the proposed equivalent model numerically. We also give the convergence analysis of the proposed algorithm. Numerical examples are presented to demonstrate that the performance of the proposed restoration model is better than that of other testing methods in terms of visual quality and some criteria such as peak signal-to-noise ratio, structure similarity, and spatial-CIELAB color error.

Publication Details

Journal
CSIAM Transactions on Applied Mathematics
Published
2025-09-26
DOI
https://doi.org/10.4208/csiam-am.so-2023-0009
Primary Topic
Diverse Scientific and Economic Studies
Type
article
Field-Weighted Citation Impact
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article

A Hue-Preserving Color Image Restoration Model Using Saturation-Value Total Variation

CSIAM Transactions on Applied Mathematics
Diverse Scientific and Economic Studies
article

A Hue-Preserving Color Image Restoration Model Using Saturation-Value Total Variation

article en

Abstract

In this paper, we propose and develop a novel hue-preserving color image restoration model. In the proposed model, saturation-value total variation is used as the regularization term. In order to reduce hue loss during regularization, the huepreserving technique is incorporated into the proposed energy functional. We then rewrite the proposed model equivalently into a three-block separable convex version and apply an alternating direction method of multipliers based algorithm to solve the proposed equivalent model numerically. We also give the convergence analysis of the proposed algorithm. Numerical examples are presented to demonstrate that the performance of the proposed restoration model is better than that of other testing methods in terms of visual quality and some criteria such as peak signal-to-noise ratio, structure similarity, and spatial-CIELAB color error.

CSIAM Transactions on Applied Mathematics
Affordable and clean energy
Openalex Percentile: Top 35%
Diverse Scientific and Economic Studies
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