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SAR image noise suppression of BEMD by the kernel principle component analysis
- Source :
- IET Image Processing, Vol 15, Iss 1, Pp 155-165 (2021)
- Publication Year :
- 2020
- Publisher :
- Institution of Engineering and Technology (IET), 2020.
-
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.
- Subjects :
- business.industry
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Pattern recognition
QA76.75-76.765
Kernel (image processing)
Signal Processing
Principal component analysis
Photography
Image noise
Computer software
Computer Vision and Pattern Recognition
Artificial intelligence
Electrical and Electronic Engineering
TR1-1050
business
Software
Subjects
Details
- ISSN :
- 17519667 and 17519659
- Volume :
- 15
- Database :
- OpenAIRE
- Journal :
- IET Image Processing
- Accession number :
- edsair.doi.dedup.....1117fadd101e89737f78fe651325ec62