Novel approach to SVD-based image filtering improvement

提出一种提高SVd滤波性能的新方法。基于奇异值分解滤波可以有效地分析水平(垂直)方向的图像特性。根据图像的局部方向,自适应地调整待滤波区域的形状,使重采样后局部区域中的边缘垂直或水平,再对局部区域进行奇异值分解滤波;所得的结果加权平均,得到信号估计值。将这一算法应用于图像去噪,实验结果表明,新方法可以有效地提高SVd的滤波性能。A novel approach to improve the filtering efficiency of a noisy image is proposed.Image filtering based on SVD favors the denoising in the line(horizontal)and column(vertical)direction.Based on this property,the new denoising method adapts shape and size of block to local orientation before performing SVD filtering.Through over-complete representation in overlap regions,the proposed method performs well in denoising and preserving image details.国家重点基础研究发展规划(973)(No.2007CB311005);福建省自然科学基金计划资助项目(No.A0710020);厦门大学985二期信息创新平台项目(No.2004-2008)---