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Multiple Decision Model for Image Denoising in Wavelet Transform Domain  

엄일규 (밀양대학교 정보통신공학과)
김유신 (부산대학교 전자공학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.29, no.7C, 2004 , pp. 937-945 More about this Journal
Abstract
A binary decision model which is used to denoising has demerits to measure the precise ratio of signal to noise because of only a binary classification. To supplement these demerits, complex statistical model and undecimated wavelet transform are generally exploited. In this paper, we propose a noise reduction method using a multi-level decision model for measuring the ratio of noise in noisy image. The propose method achieves good denoising performance with orthogonal wavelet transform because the ratio of signal to noise can be calculated to multi-valued form. In simulation results, the proposed denoising method outperforms 0.1dB in the PSNR sense than the state of art denoising algorithms using orthogonal wavelet transform.
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