MODIS多光谱图像压缩研究

李元祥邓黎敬忠良

doi:10.3724/SP.J.1146.2007.00469

MODIS多光谱图像压缩研究

doi: 10.3724/SP.J.1146.2007.00469

李元祥邓黎敬忠良

基金项目:

国家自然科学基金(40575010)资助课题

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- 被引次数: 0
出版历程
- 收稿日期: 2007-03-29
- 修回日期: 2008-04-14
- 刊出日期: 2008-10-19

Compression for MODIS Multispectral Images

Li Yuan-xiang Deng Li Jing Zhong-liang

摘要

摘要: 为有效存储MODIS多光谱图像数据，该文提出一种基于谱间预测和整数小波变换的多光谱图像压缩算法。首先通过构造谱间最优预测器去除谱间冗余，再利用整数小波变换和SPIHT算法对预测误差图像去除空间冗余，最后进行自适应算术编码。该方法可实现MODIS多光谱图像的无损、近无损和有损压缩，取得了满意的实验结果；在不同小波基条件下与3D-SPIHT算法比较，表明了该方法的有效性。
- MODIS多光谱图像 /
- SPIHT编码 /
- 最优预测 /
- 整数小波变换
Abstract: In order to store MODIS multispectral images effectively, a new hybrid compression algorithm based on optimal inter-band prediction and integer wavelet transform is proposed. First, an optimal inter-band predictor is designed for de-correlating the spectral redundancy, and the error images are created for later use. Next, spatial redundancy is removed by using an efficient integer wavelet coding method and SPIHT algorithm. Then, the adaptive arithmetic encoder is employed for binary code stream. The proposed method can implement the lossless compression, near-lossless compression and lossy compression with high compression ratio. The experimental results show that this method is more efficient than the traditional 3D-SPIHT algorithm and other wavelet transform methods with different wavelet bases.
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参考文献(1)

[1] Kaarna A and Parkkine J. Transform based lossycompression of multispectral images[J].Pattern Analysis Applications.2001, 4(1):39-50 [2] Tang Caimu, et al.. Efficient inter-band prediction andwavelet based compression for hyperspectral imagery: Adistributed Source coding approach[C]. Data CompressionConference, Snowbird, Utah, USA, 2005: 437-446. [3] 吴铮, 何明一. 基于小波变换和分段DPCM 混合编码的多光谱遥感图像压缩算法[J].电子与信息学报.2003, 25(6):747-754浏览 [4] 付文秀, 王世刚, 高燕梅. 结合矢量量化的SPIHT 算法用于多光谱图像压缩[J]. 通信学报, 2004, 25(6): 109-114.Fu W X, Wang S G, and Gao Y M, et al.. Application ofSPIHT with vector quantization to compression ofmultispectral image. Journal of China Institute ofCommunications, 2004, 25(6): 109-114. [5] Dragotti P L, Poggi G, and Ragozini A. Compression ofmultispectral images by three-dimensional SPIHTalgorithm[J].IEEE Trans. on Geoscience and Remote Sensing.2000, 38(1):416-428 [6] 马晨光, 郭雷. 基于3 维SPIHT编码的超光谱图像压缩[J]. 量子电子学报, 2005, 22(5): 680-684.Ma C G and Guo L. Hyperspectral image compression basedon 3D SPIHT coding algorithm. Chinese Journal of QuantumElectronics, 2005, 22(5): 680-684. [7] 郭广猛. 非星历表法去除MODIS 图像边缘重叠影响的研究[J].遥感技术与应用, 2003, 18(3): 172-175.Guo G M. Eliminating bowtie effect of MODIS data withoutEphemeris. Remote Sensing Technology and Application,2003, 18(3):172-175. [8] Said A and Pealman W A. A new, fast, and efficient imagecodec based on set partitioning in hierarchical trees [J].IEEETrans. on Circuits and Systems for Video Technology.1996,6(3):243-250 [9] Wu X and Memon N. Context-based lossless interbandcompression extending CALIC [J]. IEEE Trans. on ImageProcessing, 2000, 9(6): 994-1001.

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