Title :
Permutations and prediction for lossless compression of multispectral TM images
Author_Institution :
Dept. of Geogr. & Geol., Nebraska Univ., Omaha, NE, USA
fDate :
5/1/1998 12:00:00 AM
Abstract :
This paper introduces a reversible remapping technique based on sorting permutations. The algorithm developed utilizes a remapping technique and employs linear predictive operators on a pair of band for TM images. It is shown that the algorithm produces substantial improvements in the compression ratio as compared to the results reported previously
Keywords :
data compression; geophysical signal processing; geophysical techniques; image processing; remote sensing; TM image; algorithm; geophysical measurement technique; image compression; land surface; linear predictive operator; lossless compression; multispectral remote sensing; optical imaging; permutation; permutations; prediction; remapping; satellite remote sensing; terrain mapping; Digital images; Geography; Geology; Histograms; Image coding; Image converters; Mathematics; Multispectral imaging; Sorting; Two dimensional displays;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
