A Novel Video Temporal Error Concealment Algorithm based on Moment Invariants

  • سال انتشار: 1394
  • محل انتشار: نهمین کنفرانس ماشین بینایی و پردازش تصویر ایران
  • کد COI اختصاصی: ICMVIP09_005
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 661
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نویسندگان

Seyed Mojtaba Marvasti-Zadeh

Department of Electrical and Computer Engineering, Yazd University, Yazd, Iran

Hossein Ghanei-Yakhdan

Department of Electrical and Computer Engineering, Yazd University, Yazd, Iran

Shohreh Kasaei

Department of Computer Engineering, Sharif University of Technology, Tehran, Iran

چکیده

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, the use of error concealment methods, at the decoder side, is necessary to recover the damaged 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. oreover, the proposed algorithm utilizes a novel error function based onmoment invariants to select the best candidate MV. It uses the highest neighborhood information of each candidate MB, adaptively. The experimental results show that the proposed algorithm improves the objective and subjective qualities of the reconstructed frames. The average PSNR for typical sequences increases about 2.79, 2.72, and 2.67 dB compared to the classical boundary matching, directional temporal boundary matching, and outer boundary matching algorithm, respectively

کلیدواژه ها

temporal error concealment; motion vector estimation; moment invariants; feature extraction

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