DocumentCode :
3041694
Title :
Prediction model selection for compression of satellite images
Author :
Korany, Ezzat A.
Author_Institution :
Inst. of Graduate Studies & Res., Alexandria Univ., Egypt
fYear :
1996
fDate :
19-21 Mar 1996
Firstpage :
329
Lastpage :
338
Abstract :
One major problem of lossless image compression is the lower compression ratio obtained. This is due to the wide spatial bandwidth of image pixel intensities. In this paper we describe an approach for reduction of satellite image spatial bandwidth thus improving the compression ratio. In this approach we code image pixels in a predetermined sequence, predicting each pixel´s intensity using a fixed linear combination of a fixed constellation of nearby pixels, then coding the prediction error. Computer experiments have been performed on various satellite images to evaluate the performance of different prediction models on improving the compression ratio
Keywords :
data compression; geophysical signal processing; image coding; prediction theory; remote sensing; compression ratio obtained; image pixel intensities; lossless image compression; prediction error; prediction model selection; satellite images; spatial bandwidth; Bandwidth; Computer errors; Image coding; Performance evaluation; Pixel; Predictive models; Pulse modulation; Satellite broadcasting; TV broadcasting; Transform coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Radio Science Conference, 1996. NRSC '96., Thirteenth National
Conference_Location :
Cairo
Print_ISBN :
0-7803-3656-9
Type :
conf
DOI :
10.1109/NRSC.1996.551124
Filename :
551124
Link To Document :
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