Title: MRI denoising: a sparse ICA-based dictionary learning approach
Authors: T. Arathi; C. Rahul
Addresses: Department of Electronics and Communication, LBS College of Engineering, Kasaragod, Kerala, India ' Department of Computer Science and Engineering, LBS College of Engineering, Kasaragod, Kerala, India
Abstract: Image denoising is the process of removing noise from an image and is basically a trade-off between noise removal and preservation of significant image details. This paper presents a new sparse processing-based denoising algorithm, the multi-median variance-independent component analysis (MMV-ICA) denoising algorithm. Various noises which affect medical images are also considered. The proposed denoising algorithm is based on sparse and redundant representations over learned dictionaries. MMV-ICA algorithm presented in this paper makes use of a patch-based dictionary creation method. The paper presents the results of MMV-ICA denoising technique, which are found to be in par with the existing sparse-based denoising methods.
Keywords: sparse processing; dictionary learning; image denoising; independent component analysis; ICA.
DOI: 10.1504/IJMEI.2022.123931
International Journal of Medical Engineering and Informatics, 2022 Vol.14 No.4, pp.347 - 357
Accepted: 20 Oct 2020
Published online: 05 Jul 2022 *