This paper proposes a new procedure in order to improve the performance ofblock matching and 3-D filtering (BM3D) image denoising algorithm. It isdemonstrated that it is possible to achieve a better performance than that ofBM3D algorithm in a variety of noise levels. This method changes BM3D algorithmparameter values according to noise level, removes prefiltering, which is usedin high noise level; therefore Peak Signal-to-Noise Ratio (PSNR) and visualquality get improved, and BM3D complexities and processing time are reduced.This improved BM3D algorithm is extended and used to denoise satellite andcolor filter array (CFA) images. Output results show that the performance hasupgraded in comparison with current methods of denoising satellite and CFAimages. In this regard this algorithm is compared with Adaptive PCA algorithm,that has led to superior performance for denoising CFA images, on the subjectof PSNR and visual quality. Also the processing time has decreasedsignificantly.
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