Abstract

The reconstructed images from highly compressed MPEG data have noticeable image degradations, such as blocking artifacts near the block boundaries, corner outliers at crosspoints of blocks, and ringing noise near image edges because the MPEG quantizes the transformed coefficients of 8/spl times/8 pixel blocks. A postprocessing algorithm is proposed to reduce quantization effects, such as blocking artifacts, corner outliers, and ringing noise, in MPEG-decompressed images. The proposed postprocessing algorithm reduces the quantization effects adaptively by using both spatial frequency and temporal information extracted from the compressed data. The blocking artifacts are reduced by one-dimensional (1-D) horizontal and vertical low-pass filtering (LPF), and the ringing noise is reduced by two-dimensional (2-D) signal-adaptive filtering (SAF). A comparison study of the peak signal-to-noise ratio (PSNR) and the computation complexity analysis between the proposed algorithm and the MPEG-4 VM (verification model) postprocessing algorithm is performed by computer simulation with several image sequences. According to the comparison study of PSNR and computation complexity analysis, the proposed algorithm shows better performance than the VM postprocessing algorithm, whereas the subjective image qualities of both algorithms are similar.

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