A Variational Model for Simultaneously Image Denoising and Luminance Adjustment

Wei Wang , Ruofan Liu

CSIAM Trans. Appl. Math. ›› 2022, Vol. 3 ›› Issue (3) : 428 -447.

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CSIAM Trans. Appl. Math. ›› 2022, Vol. 3 ›› Issue (3) :428 -447. DOI: 10.4208/csiam-am.SO-2021-0037
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A Variational Model for Simultaneously Image Denoising and Luminance Adjustment

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Abstract

In this paper, we propose and develop a saturation value total variation (SV-TV) regularization model for simultaneously image denoising and luminance adjustment. The idea is to propose a variational approach containing an energy functional to adjust the luminance between image patches, and the noise of the image can be removed. In the proposed model, we establish the adjustment term based on the concept of structure, luminance, and contrast similarity, and we make use of the SV-TV regularization to remove the noise simultaneously. We present an efficient and effective algorithm with convergence guaranteed to solve the proposed minimization model. Experimental results are presented to show the effectiveness of the proposed model compared with existing methods.

Keywords

Luminance adjustment / structure similarity / HSV color space / saturation / value / total variation / image denoising

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Wei Wang, Ruofan Liu. A Variational Model for Simultaneously Image Denoising and Luminance Adjustment. CSIAM Trans. Appl. Math., 2022, 3(3): 428-447 DOI:10.4208/csiam-am.SO-2021-0037

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