ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS |
Prev
Next
|
|
|
An image compression method for space multispectral time delay and integration charge coupled device camera |
Jin Long-Xu (金龙旭)a b, Zhang Ran-Feng (张然峰)b |
a Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China; b Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
|
|
Abstract Multispectral time delay and integration charge coupled device (TDICCD) image compression requires low-complexity encoder because it is usually completed on board where the energy and memory are limited. The Consultative Committee for Space Data Systems (CCSDS) has proposed an image data compression (CCSDS-IDC) algorithm which is so far most widely implemented in hardware. However, it cannot reduce spectral redundancy in multispectral images. In this paper, we propose a low-complexity improved CCSDS-IDC (ICCSDS-IDC)-based distributed source coding (DSC) scheme for multispectral TDICCD image consisting of a few bands. Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in original image and its wavelet transformed coefficient. The output of bit plane extractor will be encoded by a first order entropy coder. Low-density parity-check-based Slepian-Wolf (SW) coder is adopted to implement the DSC strategy. Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band.
|
Received: 27 July 2012
Revised: 11 December 2012
Accepted manuscript online:
|
PACS:
|
42.30.Va
|
(Image forming and processing)
|
|
Fund: Project supported by the National High Technology Research and Development Program of China (Grant No. 863-2-5-1-13B). |
Corresponding Authors:
Li Jin
E-mail: jinlicareer@yahoo.com.cn
|
Cite this article:
Jin Long-Xu (金龙旭), Zhang Ran-Feng (张然峰) An image compression method for space multispectral time delay and integration charge coupled device camera 2013 Chin. Phys. B 22 064203
|
[1] |
Li J, Jin L X, Li G N and Zhang Y 2012 J. Electron. & Inf. Technol. 34 1248
|
[2] |
Wang D J and Zhang T 2011 Chin. Phys. B 20 087202
|
[3] |
Li J, Jin L X, Li G N, Zhang K and Wang W H 2012 Spectroscopy and Spectral Analysis 32 1700
|
[4] |
Qiao N S and Zou B J 2013 Chin. Phys. B 22 014203
|
[5] |
Li J, Jin L X, Li G N, Zhang K, Wang W H, Zhang R F and Zhu P 2012 Journal of Optoelectronics: Laser 23 866
|
[6] |
Zhang X, Zheng Y G and Zhang H J 2006 Chin. Phys. 15 2185
|
[7] |
Li J, Jin L X, Han S L, Li G N and Wang W H 2012 Optics and Precision Engineering 20 1090
|
[8] |
Ian B and Joan S S 2010 IEEE Trans. Geosci. Remote Sens. 487 2854
|
[9] |
Amar A 2011 Journal of Display Technology 711 586
|
[10] |
Jerome M S 1992 IEEE International Conference on Acoustics, Speech and Signal Processing, March 23-26, 1992, Princeton, USA p. 657
|
[11] |
David T 2000 IEEE Trans. Image Process. 97 1158
|
[12] |
Tang X L and William A P 2006 Hyperspectral Data Compression (New York: Springer-Verlag) p. 273
|
[13] |
David S T and Michael W M 2002 JPEG2000: Image Compression Fundamentals, Standards, and Practice, 2nd edn. (New York: Springer) p. 101
|
[14] |
Wang X Y, Yun J J and Zhang Y L 2011 Chin. Phys. B 20 104203
|
[15] |
Pan W, Zou Y and Ao L 2008 Proceedings of 2008 3rd International Conference on Intelligent System and Knowledge Engineering, November 17, 2008, Xiamen, China, p. 1237
|
[16] |
CCSDS 2005 Image Data Compression (CCSDS-122.0-B-1 Blue Book) (Washington, DC: CCSDS) p. 11
|
[17] |
Zhang J, Li H and Chen C W 2009 Proc. ICME, July, 2009, New York, p. 141
|
[18] |
Andrea A, Mauro B, Enrico M and Filippo N 2010 IEEE Trans. Geosci. Remote Sens. 484 1892
|
[19] |
Slepian J and Wolf J 1973 IEEE Trans. Inform. Theory 19 471
|
[20] |
Wyner A and Ziv J 1976 IEEE Trans. Inform. Theory 22 1
|
[21] |
Shamai S and Verdu S 1995 Eur. Trans. Telecommu. 6 587
|
[22] |
Shamai S, Verdu S and Zamir R 1998 IEEE Trans. Inform. Theory 44 564
|
[23] |
David V, Anne A and Bernd Girod 2005 Proc. 39th Asilomar Conf. Signals, Syst. Comput. November 1, 2005, Pacific Grove, CA, p. 1203
|
[24] |
Jin Y and Lee H J 2012 IEEE Transactions on Circuits and Systems for Video Technology 227 1064
|
[25] |
Kishor S and Swapna B 2011 IEEE Transactions on Circuits and Systems for Video Technology 216 825
|
[26] |
Jose E S, Estanislau A, Josep S, Ian B, Joan S S and Aaron K 2011 First International Conference on Data Compression, Communications and Processing, June 21-24, 2011, Palinuro, p. 222
|
[27] |
Xie Y and Jing X 2009 Network Infrastructure and Digital and Content Conference, November 6-8, 2009, Beijing, China, p. 353
|
No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|