Journal
SIAM JOURNAL ON IMAGING SCIENCES
Volume 12, Issue 2, Pages 972-1000Publisher
SIAM PUBLICATIONS
DOI: 10.1137/18M1230451
Keywords
color images; total variation; quaternion; color space; regularization; image restoration
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Funding
- National Natural Science Foundation of China [11771188]
- Hong Kong Research Grant Council General Research Fund [1202715, 12306616, 12200317, 12300218]
- Hong Kong Baptist University [RC-ICRS/16-17/03]
- Natural Science Foundation of Shanghai
- Fundamental Research Funds for the Central Universities of China [22120180255, 22120180067]
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Color image restoration is one of the important tasks in color image processing. Total variation regularizaton was proposed and employed for the recovery of edges in a grayscale image. In the literature, there are several methods for extension of total variation regularization for color images, for example, based on color channel coupling and tensor regularization. The main contribution of this paper is to propose and develop a new saturation-value (SV) color total variation regularization in the hue, saturation, amd value color space instead of in the original red, green, and blue color space. The development of this SV total variation can be studied via the representation of color images in the quaternion framework for color edge detection. We will investigate the properties of the SV total variation regularization and the resulting optimization model for color image restoration. Numerical examples are presented to demonstrate that the performance of the new SV total variation is better than that of existing color image total variation methods in terms of some criteria such as PSNR, SSIM, and S-CIELAB error.
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