DocumentCode :
304780
Title :
Multispectral-image coding by spectral classification
Author :
Finelli, Marco ; Gelli, Giacinto ; Poggi, Giovanni
Author_Institution :
Dipt. di Ingegneria Elettronica, Univ. di Napoli Federico II, Italy
Volume :
1
fYear :
1996
fDate :
16-19 Sep 1996
Firstpage :
605
Abstract :
This paper addresses the problem of multispectral-image compression and proposes a new encoding scheme, based on the classification of the multispectral image into regions of homogeneous land cover. Separate regions resulting from classification are efficiently encoded by means of conventional transform coding techniques, whereas the classification information is compacted resorting to spatial prediction and Ziv-Lempel coding. Simulation results show that the proposed algorithm assures both a high compression ratio and a good reproduction quality, with a reasonable computational complexity
Keywords :
discrete cosine transforms; geophysical signal processing; image classification; image coding; image resolution; image segmentation; prediction theory; remote sensing; spectral analysis; transform coding; vector quantisation; Landsat V thematic mapper sensor; Ziv-Lempel coding; algorithm; classification information; computational complexity; high compression ratio; homogeneous land cover regions; image reproduction quality; multispectral image classification; multispectral image coding; multispectral image compression; simulation results; spatial prediction; spectral classification; transform coding; vector quantization; Computational complexity; Computational modeling; Encoding; Image coding; Multispectral imaging; Remote monitoring; Remote sensing; Sorting; Spatial resolution; Transform coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
Type :
conf
DOI :
10.1109/ICIP.1996.560935
Filename :
560935
Link To Document :
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