JOURNAL ARTICLE

<title>Spatial-domain resolution-scalable video coding</title>

Atul PuriAndria H. Wong

Year: 1993 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 2094 Pages: 718-729   Publisher: SPIE

Abstract

Scalable video coding is important in a number of applications where video needs to be decoded and displayed at a variety of resolution scales. In this paper, we investigate the spatial-domain approach for spatial resolution scalability. We employ the framework proposed for the ongoing second phase of Moving Picture Experts Group (MPEG-2) standard to introduce a general coding structure and discuss key issues in progressive-to-interlace and interlace-to-interlace scalable coding. We discuss the technique of spatio-temporal weighted prediction and show detailed encoder and decoder structures employing this technique. In our simulations we focus on 2-layer progressive-to-interlace spatially scalable coding and compare its performance with the simulcast technique at different bit-rates. Next, we evaluate the performance of spatially scalable coding for different picture types. Finally, we examine the efficiency of a chosen set of weight codes in spatio-temporal weighted prediction and propose improvements.

Keywords:
Computer science Encoder Scalability Interlacing Coding (social sciences) Scalable Video Coding Image resolution Coding tree unit Context-adaptive binary arithmetic coding Entropy encoding Computer engineering Algorithm Computer architecture Decoding methods Artificial intelligence Data compression Mathematics Database

Metrics

24
Cited By
1.69
FWCI (Field Weighted Citation Impact)
2
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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