Efficient wavelet-based image denoising algorithm

Characterising the statistics of wavelet coefficients is a critical issue in image compression and denoising. Many powerful approaches have been investigated, but accurate modelling suffers from high computational complexity. In this work an efficient adaptive algorithm to capture the dependency of both inner and inter scale wavelet coefficients is proposed. Experimental results show that compared with other algorithms, in the case of higher noise variance, greater PSNR performance gain may be obtained