Mutual information-based context template modeling for bitplane coding in remote sensing image compression

Yongfei Zhang; Haiheng Cao; Hongxu Jiang; Bo Li

doi:10.1117/1.JRS.10.025011

2 May 2016 Mutual information-based context template modeling for bitplane coding in remote sensing image compression

Yongfei Zhang, Haiheng Cao, Hongxu Jiang, Bo Li

Author Affiliations +

Funded by: National Hi-Tech Research and Development Program (863 Program) of China, National Natural Science Foundation of China, NSFC

Journal of Applied Remote Sensing, Vol. 10, Issue 2, 025011 (May 2016). https://doi.org/10.1117/1.JRS.10.025011

Abstract

As remote sensing image applications are often characterized with limited bandwidth and high-quality demands, higher coding performance of remote sensing images are desirable. The embedded block coding with optimal truncation (EBCOT) is the fundamental part of JPEG2000 image compression standard. However, EBCOT only considers correlation within a sub-band and utilizes a context template of eight spatially neighboring coefficients in prediction. The existing optimization methods in literature using the current context template prove little performance improvements. To address this problem, this paper presents a new mutual information (MI)-based context template selection and modeling method. By further considering the correlation across the sub-bands, the potential prediction coefficients, including neighbors, far neighbors, parent and parent neighbors, are comprehensively examined and selected in such a manner that achieves a nice trade-off between the MI-based correlation criterion and the prediction complexity. Based on the selected context template, a high-order prediction model, which jointly considers the weight and the significance state of each coefficient, is proposed. Experimental results show that the proposed algorithm consistently outperforms the benchmark JPEG2000 standard and state-of-the-art algorithms in term of coding efficiency at a competitive computational cost, which makes it desirable in real-time compression applications, especially for remote sensing images.

Citation Download Citation

Yongfei Zhang, Haiheng Cao, Hongxu Jiang, and Bo Li "Mutual information-based context template modeling for bitplane coding in remote sensing image compression," Journal of Applied Remote Sensing 10(2), 025011 (2 May 2016). https://doi.org/10.1117/1.JRS.10.025011

Published: 2 May 2016

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