@Article{CSIAM-AM-3-3,
author = {Wei, Wang and Ruofan, Liu},
title = {A Variational Model for Simultaneously Image Denoising and Luminance Adjustment},
journal = {CSIAM Transactions on Applied Mathematics},
year = {2022},
volume = {3},
number = {3},
pages = {428--447},
abstract = {<p style="text-align: justify;">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.</p>},
issn = {2708-0579},
doi = {https://doi.org/10.4208/csiam-am.SO-2021-0037},
url = {https://global-sci.com/article/82324/a-variational-model-for-simultaneously-image-denoising-and-luminance-adjustment}
}