Image denoising based on support vector value and directional filter bank
基于支持向量值和方向滤波器组的图像去噪*

In order to denoise image, this paper proposed a new method based on support vector value and undecimated directional filter bank. The proposed algorithm is used to decompose noise images at multi-scale and multi-direction by support vector value directional filter bank(SVDFB). It is considered that the coefficients statistic characteristic of test image by SVDFB obey general Gaussian distribution, so local adaptive Bayes shrinkage factor is adopted. The simulation results and experimental analysis show that the proposed algorithm outperforms in both Peak Signal-to-Noise Ratio(PSNR) and visual quality, and effectively preserves texture and detail information of original images.