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Author:

Wang, Jin (Wang, Jin.) | Shi, Yunhui (Shi, Yunhui.) (Scholars:施云惠) | Ding, Wenpeng (Ding, Wenpeng.) | Yin, Baocai (Yin, Baocai.) (Scholars:尹宝才)

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CPCI-S

Abstract:

Intra prediction plays an important role in reducing the spatial redundancy for intra frame encoding in H.264/AVC. In this paper, we propose a low-rank matrix completion based intra prediction to improve the prediction efficiency. According to the low-rank matrix completion theory, a low-rank matrix can be exactly recovered from quite limited samples with high probability under mild conditions. After moderate rearrangement and organization, image blocks can be represented as low-rank or approximately low-rank matrix. The intra prediction can then be formulated as a matrix completion problem, thus the unknown pixels can be inferred from limited samples with very high accuracy. Specifically, we novelly rearrange the encoded blocks similar to the current block to generate an observation matrix, from which the prediction can be obtained by solving a low-rank minimization problem. Experimental results demonstrate that the proposed scheme can achieve averagely 5.39% bit-rate saving for CIF sequences and 4.21% for QCIF sequences compared with standard H.264/AVC.

Keyword:

Author Community:

  • [ 1 ] [Wang, Jin]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China
  • [ 2 ] [Shi, Yunhui]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China
  • [ 3 ] [Ding, Wenpeng]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China
  • [ 4 ] [Yin, Baocai]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China

Reprint Author's Address:

  • [Wang, Jin]Beijing Univ Technol, Coll Comp Sci & Technol, Beijing Key Lab Multimedia & Intelligent Software, Beijing 100124, Peoples R China

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Source :

2011 IEEE 13TH INTERNATIONAL WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING (MMSP)

ISSN: 2163-3517

Year: 2011

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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