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A novel video temporal error concealment algorithm based on moment invariants

Marvasti Zadeh, S. M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1109/IranianMVIP.2015.7397495
  3. Publisher: IEEE Computer Society
  4. Abstract:
  5. 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
  6. Keywords:
  7. Algorithms ; Computer vision ; Error detection ; Errors ; Extraction ; Feature extraction ; Image coding ; Image compression ; Image matching ; Multimedia services ; Video recording ; Error concealment ; Moment invariant ; Neighborhood information ; Reliable communication ; Temporal error concealment ; Temporal error concealment algorithm ; Transmission error ; Image processing
  8. Source: 9th Iranian Conference on Machine Vision and Image Processing, 18 November 2015 through 19 November 2015 ; Volume 2016-February , 2015 , Pages 20-23 ; 21666776 (ISSN) ; 9781467385398 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/7397495