关键词: 图像处理, 图像去噪, 冗余Bandelet变换, 自适应多阈值, 几何正则性

Abstract: Acording to the character of second bandelet transform，a novel image denoising scheme is proposed by combining redundant version with multi-level thresholding based on blocks.Bandelet transform is able to achieve optimal approximation and represent image of sparse for utilizing image geometrical regularity.Standard bandelet transform is lack of translation-invariation，a new version with redundant is presented.During bandeletization，thresholding estimating with no risk is introduced to reduce influence of noise on geometrical flow，and then make use of Bayes shrinkage denoising in bandelet domain.The numerical experiments indicated that the redundant approach with adaptive thresholding for image denoising is much better than wavelet and curvelet also contourelet.Especially，Bandelet denoising can preserve much more details of the images and have better visual quality because of no Psedudo-Gibbs.

Key words: image processing, image denoising, redundant Bandelet transform, adaptive multi-thresholding, geometry regularity