Multistage lattice vector quantization for hyperspectral image compression

被引：0

作者：

Liu, Ying ^{[1
]}

Pearlman, William A. ^{[1
]}

机构：

[1] Rensselaer Polytech Inst, Dept Elect Comp & Syst Engn, Ctr Image Proc Res, Troy, NY USA

来源：

CONFERENCE RECORD OF THE FORTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1-5 | 2007年

关键词：

lattice vector quantization; SPIHT algorithm; successive refinement; volume image compression;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Lattice vector quantization (LVQ) offers substantial reduction in computational load and design complexity due to the lattice regular structure [1]. In this paper, we extended the SPIHT [2] coding algorithm with lattice vector quantization to code hyperspectral. images. In the proposed algorithm, multistage lattice vector quantization (MLVQ) is used to exploit correlations between image slices, while offering successive refinement with low coding complexity and computation. Different four-dimensional lattices and significance metrics are considered. Their rate-distortion performance is compared with other 2D and 3D wavelet-based image compression algorithms.

引用

页码：930 / 934

页数：5

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