Image and Signal Processing Methods

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

[+] Author Affiliations
Yongfei Zhang, Hongxu Jiang, Bo Li

Beihang University, Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beijing 100191, China

Beihang University, State Key Laboratory of Virtual Reality Technology and Systems, Beijing 100191, China

Haiheng Cao

Beihang University, Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beijing 100191, China

J. Appl. Remote Sens. 10(2), 025011 (May 02, 2016). doi:10.1117/1.JRS.10.025011
History: Received January 22, 2016; Accepted April 11, 2016
Text Size: A A A

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.

Figures in this Article
© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Yongfei Zhang ; Haiheng Cao ; Hongxu Jiang and Bo Li
"Mutual information-based context template modeling for bitplane coding in remote sensing image compression", J. Appl. Remote Sens. 10(2), 025011 (May 02, 2016). ; http://dx.doi.org/10.1117/1.JRS.10.025011


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.