Abstract :
Nowadays, the use of multimedia services such as video sequences is constantly growing. Unfortunately, due to the lack of reliable communication channels and video data sensitivity to transmission errors, the quality of received video might decrease. Therefore, decoder error concealment methods have been developed to retrieve the damaged or lost data. In this paper, a novel temporal error concealment (TEC) algorithm based on moment invariants is presented. It includes three main stages of: designation of candidate motion vectors (MVs) set, adaptive determination of block size in the current and reference frames for feature extraction, and error function calculation based on moment invariants. The proposed algorithm uses different block sizes, proportional to the area of each candidate macro-block (MB), for a better feature extraction. Moreover, the proposed algorithm utilizes a novel error function based on moment invariants to select the best candidate MV. It uses the highest neighborhood information of each candidate MB, adaptively. The obtained results from video test sequences demonstrate that the proposed algorithm achieves better-modified frames, which have the higher average PSNR of about 2.79, 2.72, and 2.67 dB compared with the classical boundary matching, directional temporal boundary matching, and outer boundary matching algorithm, respectively.
