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