Brain Image Enhancement Approach Based on Singular Value Decomposition in Nonsubsampled Shearlet Transform Domain
In this work, a novel image enhancement algorithm using NSST and SVD is proposed to improve the definition of the acquired brain images. The input brain image is computed by CLAHE, then the processed brain image and input brain image are decomposed into low- and high-frequency components
by NSST, the singular value matrix of the low-frequency component is estimated. The final enhancement image is obtained by inverse NSST. Results of this experiment demonstrate that the proposed technique has good performance in terms of brain image enhancement when compared to other methods.
Keywords: Brain Image; CLAHE; Image Enhancement; NSST; SVD
Document Type: Research Article
Affiliations: 1: School of Electronic Information Engineering, Zhuhai College of Jilin University, Zhuhai 519041, China 2: School of Mathematics and Information Science, Xinxiang University, Xinxiang 453003, China 3: College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China 4: Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
Publication date: 01 August 2020
- Journal of Medical Imaging and Health Informatics (JMIHI) is a medium to disseminate novel experimental and theoretical research results in the field of biomedicine, biology, clinical, rehabilitation engineering, medical image processing, bio-computing, D2H2, and other health related areas.
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