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Proceedings Paper

Lossless compression of images from China-Brazil Earth Resources Satellite
Author(s): Marcelo S. Pinho
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Paper Abstract

The aim of this work is to evaluate the performance of different schemes of lossless compression when applied to compact images collected by the satellite CBERS-2B. This satellite is the third one constructed under the CBERS Program (China- Brazil Earth Resources Satellite) and it was launched in 2007. This work focuses in the compression of images from the CCD camera which has a resolution of 20 x 20 meters and five bands. CBERS-2B transmits the data from CCD in real time, with no compression and it does not storage even a small part of images. In fact, this satellite can work in this way because the bit rate produced by CCD is smaller than the transmitter bit rate. However, the resolution and the number of spectral bands of imaging systems are increasing and the constrains in power and bandwidth bound the communication capacity of a satellite channel. Therefore, in the future satellites the communication systems must be reviewed. There are many algorithms for image compression described in the literature and some of them have already been used in remote sensing satellites (RSS). When the bit rate produced by the imaging system is much higher than the transmitter bit rate, a lossy encoder must be used. However, when the gap between the bit rates is not so high, a lossless procedure can be an interesting choice. This work evaluates JPEG-LS, CALIC, SPIHT, JPEG2000, CCSDS recommendation, H.264, and JPEG-XR when they are used to compress images from the CCD camera of CBERS-2B with no loss. The algorithms are applied in a set of twenty images with 5, 812 x 5, 812 pixels, running in blocks of 128 x 128; 256 x 256; 512 x 512; and 1, 024x1, 024 pixels. The tests are done independently in each original band and also in five transformed bands, obtained by a procedure which decorrelates them. In general, the results have shown that algorithms based on predictive schemes (CALIC and JPEG-LS) applied in transformed decorrelated bands produces a better performance in the mean. Furthermore, as expected, the performance improves when the block length increases. Since the compression rate is variable for each block, it is important to evaluate the distribution of this parameter. Preliminary results have shown that the distributions are quite similar for all algorithms.

Paper Details

Date Published: 27 October 2011
PDF: 8 pages
Proc. SPIE 8180, Image and Signal Processing for Remote Sensing XVII, 81801A (27 October 2011); doi: 10.1117/12.898065
Show Author Affiliations
Marcelo S. Pinho, Instituto Tecnológico de Aeronáutica (Brazil)


Published in SPIE Proceedings Vol. 8180:
Image and Signal Processing for Remote Sensing XVII
Lorenzo Bruzzone, Editor(s)

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