SAR image noise suppression of BEMD by the kernel principle component analysis. Issue 1 (6th December 2020)

• Record Type: Journal Article
• Authors: Huang, Changjun; Zhou, Xinghua; Hu, Jiyuan; Zhou, Qingshan
• Is Part Of: IET image processing. Volume 15:Issue 1(2021)
• Page Start: 155
• Page End: 165
• Publication Date: 2020-12-06
• Subjects: Image processing -- Periodicals; 621.36705
• DOI: 10.1049/ipr2.12015
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract: In the process of synthetic aperture radar image noise suppression by the bi‐dimensional empirical mode decomposition (BEMD) algorithm, the edge effect is a key problem in the BEMD operation. To weaken this effect, an improved BEMD‐kernel principal component analysis (BEMD‐KPCA) method of image denoising is proposed in this study. Experimental results show that the BEMDKPCA algorithm has a good capability of improving edge effects in the BEMD decomposition process and satisfying the requirement of the reliable decomposition results. Compared with the traditional BEMD method, the proposed approach has a good effect on suppressing speckle noise. Additionally, the denoised image from the decomposed components of the IMFs processed by the BEMD‐KPCA method sufficiently preserves the edge and detail information, confirming its high coherency with the original image.