LOW-COMPLEXITY LOSSY COMPRESSION OF HYPERSPECTRAL IMAGES VIA INFORMED QUANTIZATION

被引：8

作者：

Abrardo, Andrea ^{[1
]}

Barni, Mauro ^{[1
]}

Magli, Enrico ^{[2
]}

机构：

[1] Univ Siena, Dipartimento Ingn Informaz, I-53100 Siena, Italy

[2] Politecn Torino, Dipartimento Elettr, Turin, Italy

来源：

2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING | 2010年

关键词：

D O I：

10.1109/ICIP.2010.5651256

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Lossy compression of hyperspectral and ultraspectral images is traditionally performed using 3D transform coding. This approach yields good performance, but the complexity and memory requirements make it unsuitable for onboard compression. In this paper we propose a low-complexity lossy compression scheme based on prediction, quantization and rate-distortion optimization. The scheme employs coset codes coupled with the new concept of "informed quantization", and requires no entropy coding. The performance of the resulting algorithm is competitive with that of state-of-the-art 3D transform coding schemes, but the complexity is immensely lower, making it suitable for onboard compression at high throughputs.

引用

页码：505 / 508

页数：4

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