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
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