快速仿射非局部均值图像去噪

Fast affine non-local means image denosing

针对仿射非局部均值(ANLM)算法对图像去噪过程中出现用时过长的问题,提出了一种快速仿射非局部均值去噪(F-ANLM)算法。通过对算法的研究和用时分析得知,仿射变换和关于仿射不变相似性度量的计算这2个模块占时最多,因此从这2个部分入手提出优化策略。算法首先使用仿射协变结构张量其特征向量的夹角代替尺寸不变特征变换(SIFT)算子的主方向,简化了仿射变换过程;然后将ANLM方法中的仿射不变相似性度量改写为离散卷积的形式,使用快速傅里叶变换减少卷积的运算量,加速仿射协变特征区域之间相似性度量的计算。实验证明,F-ANLM方法简化了仿射变换和仿射不变相似性度量的计算,与原来ANLM算法相比,速度得到很大的提升。

To address the problem of high time consumption of the affine non-local mean(ANLM)algorithm in the denoising process,a fast affine non-local mean denoising(F-ANLM)algorithm was proposed.Through time analysis of the affine non-local mean algorithm,it was known that the two modules,the affine transformation and the calculation of the affine invariant similarity measure,were the most time-consuming.Therefore,the optimization strategy was proposed from these tworegards.The algorithm first employed the included angle of the feature vector of the affine covariant structure tensor instead of the main direction of the SIFT operator,and then rewrote the affine invariant similarity measure in the ANLM method into the form of discrete convolution.In addition,the Fast Fourier Transform was adopted to reduce the amount of convolution operation and accelerate the calculation of similarity measures between affine covariant feature regions.Experiments show that the F-ANLM algorithm can simplify the calculation of affine transformation and affine invariant similarity measures,and greatly increase the speed compared with the original ANLM algorithm.