Paper
1 October 2011 Simple and efficient remote sensing image transformation for lossless compression
Farshid Sepehrband, Pedram Ghamisi, Mohammad Mortazavi, Jeiran Choupan
Author Affiliations +
Proceedings Volume 8285, International Conference on Graphic and Image Processing (ICGIP 2011); 82854A (2011) https://doi.org/10.1117/12.913262
Event: 2011 International Conference on Graphic and Image Processing, 2011, Cairo, Egypt
Abstract
Remote Sensing (RS) images or satellite images include information about earth. Compression of RS images is important in the field of satellite transmission systems and mass storage purposes. Because of importance of information and existent of large amount of details, lossless compression preferred. Real time compression technique is applied on satellite and aerial transmission systems [1]. A simple algorithm accelerates the whole process in real time purposes. Lossless JPEG, JPEG-LS and JPEG2000 are some famous lossless compression methods. Transformation is the first step of these methods. In this paper, a simple and efficient method of lossless image transformation has been introduced by improving prediction ability which leads to more energy compaction. After mathematical proof for efficiency of new method, it compared with previous transformations of JPEG and JPEG2000 respectively by comparing their entropy value. Finally, we conclude that, our new method is cost effective for real time applications.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Farshid Sepehrband, Pedram Ghamisi, Mohammad Mortazavi, and Jeiran Choupan "Simple and efficient remote sensing image transformation for lossless compression", Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82854A (1 October 2011); https://doi.org/10.1117/12.913262
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Cited by 3 scholarly publications.
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KEYWORDS
Image compression

Remote sensing

JPEG2000

Satellites

Discrete wavelet transforms

Satellite imaging

Image storage

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