Synthetic aperture radar (SAR) instruments on spacecraft are capable of producing huge quantities of data.
Onboard lossy data compression is commonly used to reduce the burden on the communication link. In this
paper an overview is given of various SAR data compression techniques, along with an assessment of how much
improvement is possible (and practical) and how to approach the problem of obtaining it.
A low-complexity, adaptive predictive technique for lossless compression of hyperspectral imagery is described. This technique is designed to be suitable for implementation in hardware such as a field programmable gate array (FPGA); such an implementation could be used for high-speed compression of hyperspectral imagery onboard a spacecraft. The predictive step of the technique makes use of the sign algorithm, which is a relative of the least mean square (LMS) algorithm from the field of low-complexity adaptive filtering. The compressed data stream consists of prediction residuals encoded using a method similar to that of the JPEG-LS lossless image compression standard. Compression results are presented for several datasets including some raw Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) datasets and raw Atmospheric Infrared Sounder (AIRS) datasets. The compression effectiveness obtained with the technique is competitive with that of the best of previously described techniques with similar complexity.
We present a novel data compression technique, called recursive interleaved entropy coding, that is based on recursive interleaving of variable-to variable length binary source codes. A compression module implementing this technique has the same functionality as arithmetic coding and can be used as the engine in various data compression algorithms. The encoder compresses a bit sequence by recursively encoding groups of bits that have similar estimated statistics, ordering the output in a way that is suited to the decoder. As a result, the decoder has low complexity. The encoding process for our technique is adaptable in that each bit to be encoded has an associated probability-of-zero estimate that may depend on previously encoded bits; this adaptability allows more effective compression. Recursive interleaved entropy coding may have advantages over arithmetic coding, including most notably the admission of a simple and fast decoder. Much variation is possible in the choice of component codes and in the interleaving structure, yielding coder designs of varying complexity and compression efficiency; coder designs that achieve arbitrarily small redundancy can be produced. We discuss coder design and performance estimation methods. We present practical encoding and decoding algorithms, as well as measured performance results.
Conference Committee Involvement (5)
Satellite Data Compression, Communications, and Processing VIII
12 August 2012 | San Diego, California, United States
Satellite Data Compression, Communications, and Processing VII
23 August 2011 | San Diego, California, United States
Satellite Data Compression, Communications, and Processing VI
3 August 2010 | San Diego, California, United States
Satellite Data Compression, Communication, and Processing V
4 August 2009 | San Diego, California, United States
Satellite Data Compression, Communication, and Processing IV
10 August 2008 | San Diego, California, United States
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