alexa A NOVEL SCANNING SCHEME FOR DIRECTIONAL SPATIAL PREDICTION OF AVS INTRA CODING
ISSN ONLINE(2278-8875) PRINT (2320-3765)

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering
Open Access

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Research Article

A NOVEL SCANNING SCHEME FOR DIRECTIONAL SPATIAL PREDICTION OF AVS INTRA CODING

Md. Salah Uddin Yusuf1, Mohiuddin Ahmad2
  1. Assistant Professor, Dept. of EEE, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh
  2. Professor, Dept. of EEE, Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh
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Abstract

Transform coefficient scan is an important procedure of video coding. In video coding standards such as MPEG2, MPEG4, H.264/AVC and AVS, there are zigzag scan for frame coding and field scan for field coding. In this paper, a novel scanning scheme (Z-Scan) of AVS for intra-prediction coding is proposed. In traditional zigzag scanning the fixed scan pattern is used, which has designed to organize quantized transform coefficients in order to bring the high-frequency components as more as possible, so that the coefficients can be encoded more efficiently using the entropy encoding. However, zigzag scan cannot efficiently organize the transform coefficients due to different residual energy distribution produced by different intra prediction. To resolve this problem, in this paper, we propose a new zscan scheme to further improve intra coding efficiency for the AVS standard. In this method, traditional zigzag scan, horizontal z-scan, and vertical z-scan are used depending on the spatial prediction directions. It is relatively easy to implement our z-scan scheme into AVS codec without changing the syntax. Experimental results demonstrate that the z-scan scheme can remarkably reduce bitrates by approximately 2.1% compared with AVS codec using zigzag scan, while the PSNR of video sequences are maintained. Simulation results show that the proposed adaptive coefficient scanning scheme can achieve significant compression improvement.

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