Research Article
Low-Complexity and High-Quality Image Compression Algorithm for Onboard Satellite
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 47 - Issue 17 |
| Published: June 2012 |
| Authors: Sujata Swamy, Mamatha A.S, Vipula Singh |
10.5120/7282-0395
|
Sujata Swamy, Mamatha A.S, Vipula Singh . Low-Complexity and High-Quality Image Compression Algorithm for Onboard Satellite. International Journal of Computer Applications. 47, 17 (June 2012), 24-31. DOI=10.5120/7282-0395
@article{ 10.5120/7282-0395,
author = { Sujata Swamy,Mamatha A.S,Vipula Singh },
title = { Low-Complexity and High-Quality Image Compression Algorithm for Onboard Satellite },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 47 },
number = { 17 },
pages = { 24-31 },
doi = { 10.5120/7282-0395 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Sujata Swamy
%A Mamatha A.S
%A Vipula Singh
%T Low-Complexity and High-Quality Image Compression Algorithm for Onboard Satellite%T
%J International Journal of Computer Applications
%V 47
%N 17
%P 24-31
%R 10.5120/7282-0395
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Image Compression reduces redundancy in data representation in order to achieve saving in the cost of storage and transmission. Image compression compensates for the limited on-board resources, in terms of mass memory and downlink bandwidth and thus it provides a solution to the "bandwidth vs. data volume" dilemma of modern spacecraft. Thus compression is very important feature in payload image processing units of many satellites. A low complexity and high efficiency near-lossless image compression algorithm is suggested in this paper. The algorithm provides the average compression ratio of 1. 403 with high image quality for lossless compression. Compression ratio increases as ? parameter increases. Using proposed algorithm compression ratio of 4. 208 is achieved for near-lossless compression. The proposed algorithm has low memory cost suitable for hardware implementation.
References
- Sujatha S. Swamy, Mamatha A. S, Vipula Singh, "Satellite Image Compression Techniques", National Conference on Computational Intelligence & Applications (NCCIA) accepted 6th Feb 2012.
- Guoxia Yu, Tanya Vladimirova, MartinN. Sweeting "Image compression systems on board satellites" Surrey Space Centre, University of Surrey, Guildford, Surrey GU27XH, UK Surrey Satellite Technology Limited, Tyco House, Stephenson Road, Surrey Research Park, Guild ford GU27YE, UK accepted 16 December 2008.
- M. Klimesh, V. Stanton, and D. Watola, "Hardware implementation of a lossless image compression algorithm using a field programmable gate array," NASA JPL, California Inst. Technol. , Pasadena, 2001.
- Guoxia Yu; Vladimirova, T. ; Sweeting, M. N. ; Surrey Space Centre, Univ. of Surrey, Guildford, UK "FPGA-based onboard multi/hyperspectral image compression system" in Geoscience and Remote Sensing Symposium, IEEE International, IGARSS 12-17 July 2009.
- Nunez-Yanez, J. L et al. "Statistical Lossless Compression of Space Imagery and General Data in a Reconfigurable Architecture" in: Adaptive Hardware and Systems, 2008. AHS '08. NASA/ESA Conference on 22-25 June 2008.
- Pizzolante, R. ; Dipt. di Inf. ed Applicazioni R. M. Capocelli, Univ. degli Studi di Salerno, Fisciano, Italy "Lossless Compression of Hyperspectral Imagery" in Data Compression, Communications and Processing (CCP), First IEEE International Conference on 21-24 June 2011.
- Takada, J. ; et al. , "A Fast Progressive Lossless Image Compression Method for Space and Satellite Images" in Geo-science and Remote Sensing Symposium, IGARSS IEEE International on 23-28 July 2007.
- Ze Wang, et. al. "A High Performance Fully Pipelined Architecture for Lossless Compression of Satellite Image", in Multimedia Technology (ICMT), International Conference on 29-31 Oct. 2010IEEE.
- Cheng-Chen Lin; Yin-Tsung Hwang; Dept. of Electr. Eng. , Nat. Chung Hsing Univ. , Taichung, Taiwan "An Efficient Lossless Compression Scheme for Hyperspectral Images Using Two-Stage Prediction" in Geoscience and Remote Sensing Letters, IEEE on July 2010 Volume:7, Issue-3.
- Xiang Xie, Guolin Li, and Zhihua Wang, "A Low-Complexity and High-Quality Image Compression Method for Digital Cameras" received Aug. 18, 2005; ETRI Journal, Volume 28, Number 2, April 2006.
- M. J. Weinberger, G. Seroussi, and G. Sapiro, "LOCO-I: A Low Complexity, Context-Based, Lossless Image Compression Algorithm," Proc. of the 1996 Data Compression Conference (DCC'96), Snowbird, Utah, pp. 141-149, March 1996.
- M. Weinberger and G. Seroussi, "From LOCO-I to the JPEG-LS standard," HP Laboratories, Palo Alto, CA, 1999. [Online]. Available: http://www. hpl. hp. com/techreports/1999/HPL-1999-3. pdf
- M. Weinberger, G. Sapiro, and G. Seroussi, "The LOCO-I lossless image compression algorithm: Principle and standardization into JPEGLS," IEEE Trans. Image Process. , vol. 9, no. 8, pp. 1309-1324, Aug. 2000.
- M. Ferretti and M. Boffadossi, "A parallel pipelined implementation of LOCO-I for JPEG-LS," in Proc. ICPR, 2004, vol. 1, pp. 769–772.
- Xiaowen Li, Xinkai Chen, Xiang Xie, Guolin Li, Li Zhang, Chun Zhang, Zhihua Wang, "A Low Power, Fully Pipelined JPEG-LS Encoder for Lossless Image Compression" ICME 2007, pp. 1906 1909,2007.
- Markos Papadonikolakis, et. al, "Efficient High-Performance ASIC Implementation of JPEG-LS Encoder", received on 29 May 2007;
- Chien Wen Chen et. al, "A Modified JPEG-LS Image Compression Scheme for Low Bit-Rate Application", in International Multi Conference of Engineers and Computer Scientists 2008 Vol I IMECS 2008, 19-21 March, 2008, Hong Kong.
- Michael Piorun, "Hardware Implementation of a JPEG-LS Codec", A Thesis Submitted in 2001 in Partial Fulfilment of the Requirements for the Degree of MASTER OF SCIENCE, In Computer. & Engineering.
Index Terms
Keywords