Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding
Joint Authors
Nian, Yongjian
He, Mi
Wan, Jianwei
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-09-30
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
A low-complexity compression algorithm for hyperspectral images based on distributed source coding (DSC) is proposed in this paper.
The proposed distributed compression algorithm can realize both lossless and lossy compression, which is implemented by performing scalar quantization strategy on the original hyperspectral images followed by distributed lossless compression.
Multilinear regression model is introduced for distributed lossless compression in order to improve the quality of side information.
Optimal quantized step is determined according to the restriction of the correct DSC decoding, which makes the proposed algorithm achieve near lossless compression.
Moreover, an effective rate distortion algorithm is introduced for the proposed algorithm to achieve low bit rate.
Experimental results show that the compression performance of the proposed algorithm is competitive with that of the state-of-the-art compression algorithms for hyperspectral images.
American Psychological Association (APA)
Nian, Yongjian& He, Mi& Wan, Jianwei. 2013. Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1010865
Modern Language Association (MLA)
Nian, Yongjian…[et al.]. Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding. Mathematical Problems in Engineering No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1010865
American Medical Association (AMA)
Nian, Yongjian& He, Mi& Wan, Jianwei. Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1010865
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1010865