JOURNAL ARTICLE

<title>Hierarchical image sequence coding with tree-structured vector quantization</title>

Uluğ BayazıtWilliam A. Pearlman

Year: 1993 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 2094 Pages: 1649-1660   Publisher: SPIE

Abstract

The paper presents two different approaches to image sequence coding which exploit the spatial frequency statistics as well as the spatial and temporal correlation present in the video signal. The first approach is the pyramidal decomposition of the Motion Compensated Frame Difference (MCFD) signal in the frequency domain and the subsequent coding by unbalanced Tree Structured Vector Quantizers (TSVQ) designed to match the statistics of the frequency bands. The type of TSVQ used in this study possess the advantage of low computational complexity with coding performance comparable to full-search vector quantization. The second approach is similar except that the order of motion estimation/compensation and pyramidal decomposition are interchanged.

Keywords:
Vector quantization Computer science Motion compensation Motion estimation Coding (social sciences) Algorithm Motion vector Sub-band coding Artificial intelligence Computational complexity theory Computer vision Pattern recognition (psychology) Theoretical computer science Speech recognition Speech coding Mathematics Image (mathematics) Statistics

Metrics

2
Cited By
0.55
FWCI (Field Weighted Citation Impact)
0
Refs
0.68
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

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

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