TY - JOUR T1 - A Variational Model for Simultaneously Image Denoising and Luminance Adjustment AU - Wang , Wei AU - Liu , Ruofan JO - CSIAM Transactions on Applied Mathematics VL - 3 SP - 428 EP - 447 PY - 2022 DA - 2022/08 SN - 3 DO - http://doi.org/10.4208/csiam-am.SO-2021-0037 UR - https://global-sci.org/intro/article_detail/csiam-am/20968.html KW - Luminance adjustment, structure similarity, HSV color space, saturation, value, total variation, image denoising. AB -
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.