Progressive scalable interactive region-of-interest image coding using vector quantization

被引：10

作者：

Ebrahimi-Moghadam, A ^{[1
]}

Shirani, S ^{[1
]}

机构：

[1] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON L8S 4K1, Canada

来源：

IEEE TRANSACTIONS ON MULTIMEDIA | 2005年 / 7卷 / 04期

关键词：

embedded coding; foveation; image compression lossy compression; region of interest; scalability; vector quantization;

D O I：

10.1109/TMM.2005.850967

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We have developed novel progressive scalable region-of-interest (ROI) image compression schemes with rate-distortion-complexity tradeoff based on vector quantization. Residual vector quantization (RVQ) equips the encoder with a multi-resolution apparatus which is useful for rate-distortion tradeoff. Having all advantages of RVQ, jointly suboptimized RVQ provides a distortion-complexity adjustment. The systems are unbalanced in the sense that the decoder has less computational requirements than the encoder. The proposed jointly suboptimized RVQ method provides an interactive tool for fast ROI-based browsing from image archives.

引用

页码：680 / 687

页数：8

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