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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.
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