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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제19권 제3호
- 발행연도
- 2023.6
- 수록면
- 275 - 288 (14page)
- DOI
- 10.3745/JIPS.04.0277
이용수
초록· 키워드
오류제보하기
Many image edge details are easily lost in the image denoising process, and the smooth image regions are proneto produce jagged. In this paper, we propose a wavelet-based image global k- singular value decompositionvariational method to remove image noise. A layer of wavelet decomposition is applied to the noisy image first. Then, the image global k-singular value decomposition (IGK-SVD) method is used to remove the random noiseof low-frequency components. Furthermore, a constructed variational denoising method (VDM) removes therandom noise in the high-frequency component. Finally, the denoised image is obtained by wavelet reconstruction. The experimental results show that the proposed method's peak signal-to-noise ratio (PSNR) value ishigher than other methods, and its structural similarity (SSIM) value is closer to one, indicating that theproposed method can effectively suppress image noise while retaining more image edge details. The denoisedimage has better denoising effects.
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