Proceedings Article | 5 March 2008
KEYWORDS: Image compression, Image processing, Image storage, Relativity, Data acquisition, Data storage
This paper presents an algorithm based on mixing transform of wave band grouping to eliminate spectral redundancy, the
algorithm adapts to the relativity difference between different frequency spectrum images, and still it works well when
the band number is not the power of 2. Using non-boundary extension CDF(2,2)DWT and subtraction mixing transform
to eliminate spectral redundancy, employing CDF(2,2)DWT to eliminate spatial redundancy and SPIHT+CABAC for
compression coding, the experiment shows that a satisfied lossless compression result can be achieved. Using
hyper-spectral image Canal of American JPL laboratory as the data set for lossless compression test, when the band
number is not the power of 2, lossless compression result of this compression algorithm is much better than the results
acquired by JPEG-LS, WinZip, ARJ, DPCM, the research achievements of a research team of Chinese Academy of
Sciences, Minimum Spanning Tree and Near Minimum Spanning Tree, on the average the compression ratio of this
algorithm exceeds the above algorithms by 41%,37%,35%,29%,16%,10%,8% respectively; when the band number is the
power of 2, for 128 frames of the image Canal, taking 8, 16 and 32 respectively as the number of one group for
groupings based on different numbers, considering factors like compression storage complexity, the type of wave band
and the compression effect, we suggest using 8 as the number of bands included in one group to achieve a better
compression effect. The algorithm of this paper has priority in operation speed and hardware realization convenience.
