Optimized vector bilateral filter for multispectral image denoising

Vector bilateral filtering has been shown to provide several advantages in processing hyperspectral images such as good noise removal while minimizing edge degradation, and dynamic range enhancement of bands with impaired signal to noise ratios. This paper introduces an approach for selection of the parameters of a vector bilateral filter through an optimization procedure rather than by ad hoc means. The approach is based on posing the filtering problem as one of nonlinear estimation and minimizing the Stein´s unbiased risk estimate (SURE) of this nonlinear estimator. Experimental results show that the optimized vector bilateral filter provides improved denoising performance on multispectral images when compared to several other approaches.