Postprocessing in block-based video coding based on a quantization noise model

In this paper, we propose a postprocessing method based on a quantization noise model with some assumptions in wavelet domain to reduce the blocking and ringing artifacts in block-coded video sequences. The quantization noise is considered as the sum of the blocking noise and the remainder noise including ringing noise. Since the one-dimensional (1-D) wavelet transform (WT) used in this paper represents a regularized differentiation, the blocking noise which is a gray level discontinuity at each block boundary appears as an impulse. We model the impulse as the blocking noise in wavelet domain and reduce it by estimating and weakening the strength of each blocking noise component that appears as an impulse at the block boundary in wavelet domain. The impulse strength estimation is performed using median filter, quantization parameter (QP), and local activity. The remainder noise, which is considered as a white Gaussian noise at non-edge pixels, then is reduced by soft-thresholding. Experimental results show that the proposed method yields better performance over verification model (VM) post-filter in MPEG-4 for all test sequences of various compression ratios.