An iterative blocking artifact reduction using wavelet transform

摘要

We propose an iterative algorithm for reducing the blocking artifact in block transform-coded images by using a wavelet transform (WT). An image is considered as a set of one-dimensional (1-D) horizontal and vertical signals and 1-D WT is utilized in which the mother wavelet is the first order derivative of a Gaussian like function. The blocking artifact is reduced by removing the blocking component that causes the variance at the block boundary position in the first scale wavelet domain to be abnormally higher than those at the other positions using a minimum mean square error (MMSE) filter in the wavelet domain. This filter minimizes the MSE between the ideal blocking component-free signal and the restored signal in the neighborhood of block boundaries in the wavelet domain. It also uses local variance in the wavelet domain for pixel adaptive processing. The filtering and the projection onto a convex set of quantization constraint are iteratively performed in alternating fashion. Experimental results show that the proposed method yields not only a PSNR improvement of about 0.46-1.26 dB, but also subjective quality nearly free of the blocking artifact and edge blur.