块迭代线性预测的超光谱图像分布式压缩算法

doi:10.3969/j.issn.1001-2400.2010.04.018

J4 ›› 2010, Vol. 37 ›› Issue (4): 683-688.doi: 10.3969/j.issn.1001-2400.2010.04.018

• Original Articles • Previous Articles Next Articles

Block based iterative linear prediction at the decoder for hyper-spectral imagery compression using distributed source coding

WU Xian-yun¹;LI Yun-song¹;WU Cheng-ke¹;KONG Fan-qiang¹;LI Wen-ming²

(1. State Key Lab. of Integrated Service Networks, Xidian Univ., Xi'an 710071， China;
2. Changchun Inst. of Optics, Fine Mechanics and Physics, Chinese Academy of Sci., Changchun 130033， China)

Received:2009-05-12 Online:2010-08-20 Published:2010-10-11
Contact: WU Xian-yun E-mail:xywu@mail.xidian.edu.cn

Abstract

Abstract:

Based on the analysis of the hyper-spectral images, a new compression algorithm based on the DCT transform domain distributed source coding is proposed. Our algorithm performs the bitplane encoding at the encoder with the DCT subbands order, while using the key frame to reconstruct the side information for LDPC decoding at the decoder. Few pixels are adopted to perform linear prediction at the encoder, thus reducing the complexity. Subbands previously decoded are utilized for iterative linear prediction based on blocks at the decoder, and following subbands are decoded with optimized side information. Compared with conventional algorithms, the proposed algorithm efficiently reduces the cost of computation and memory usage at the encoder, which facilitates the hardware implementation.

Key words: hyper-spectral imagery, distributed source coding, iterative linear prediction, side information optimize

WU Xian-yun;LI Yun-song;WU Cheng-ke;KONG Fan-qiang;LI Wen-ming. Block based iterative linear prediction at the decoder for hyper-spectral imagery compression using distributed source coding[J].J4, 2010, 37(4): 683-688.

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Block based iterative linear prediction at the decoder for hyper-spectral imagery compression using distributed source coding

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