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지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2010.11
- 수록면
- 28 - 33 (6page)
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초록· 키워드
오류제보하기
A novel image noise reduction filter is developed in wavelet domain. The correlations of intensity and anisotropy of wavelet coefficients in different sub-bands and scales are utilized as features to separate signal from random noise. Dynamic thresholding is used to further increase the sensitivity and discrimination against different noise patterns and standard deviations. Simulation in Matlab is carried out by filtering an AWGN-added sub-set of test images from Kodak image data base and a standard digital Macbeth Color Chart. Average PSNR
scores of R, G and B color channels are competitive to bilateral filter and a prominent commercial noise reduction tool Neat Image. In addition, the low computational complexity of threshold operation makes it applicable for low cost implementations in various imaging devices as a real time noise reduction module.
scores of R, G and B color channels are competitive to bilateral filter and a prominent commercial noise reduction tool Neat Image. In addition, the low computational complexity of threshold operation makes it applicable for low cost implementations in various imaging devices as a real time noise reduction module.
목차
Abstract
Ⅰ. BACKGROUND
Ⅱ. WAVELET HARD THRESHOLD AND THE INTRODUCTION OF DTCIA
Ⅲ. DYNAMIC THRESHOLDING
Ⅳ. EXPERIMENTS AND RESULTS
Ⅴ. CONCLUSION AND DISCUSSIONS
Ⅵ. Acknowledgement
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2013-569-001488854