MOVING LEAST SQUARES METHOD WITH TOTAL VARIATION MINIMIZING REGULARIZATION FOR IMAGE DENOISING
Yeon Ju Lee, Sukho Lee, Jungho Yoon · 한국산업응용수학회 학술대회 논문집 · 2012
In this study, we propose a new denoising scheme, where the total variation minimizing term is adopted by the moving least squares method. In the regularity based variational approach, the resulted image is obtained as a result of the competition between the fidelity term and a certain regularity term, while in the least squares based approach the image is computed as a minimizer to a constrained least squares problem. The total variation minimizing denoising scheme is an exemplary scheme of the former approach with the total variation minimizing term as the regularity term, while the moving least squares method is an exemplary scheme of the latter approach. Both approaches have appeared in the literature of image processing independently. By putting schemes from both approaches into a single framework, the resulted scheme benefits from the advantageous properties of both parties. The resulted denoising scheme overcomes the drawbacks of both schemes, i.e., the staircase artifact in the total variation minimizing based denoising and the local boiling artifact in the moving least squares based denoising method.