Please use this identifier to cite or link to this item:
|Title:||Efficient algorithm for multispectral data coding using approximate trigonometric expansions||Authors:||Kasparis, Takis
Memon, Qurban A.
|Keywords:||Algorithms;Data processing;Satellites;Remote-sensing images;Computer systems||Issue Date:||1997||Publisher:||SPIE||Source:||Algorithms for Multispectral and Hyperspectral Imagery III, 1997, Orlando, Florida||Abstract:||Images obtained from satellite and airborne multispectral collection platforms exhibit a high degree of spatial and spectral correlations that must be properly exploited in any multispectral bandwidth compression scheme. Removing the inherent spectral correlation in the data results in a significant compaction of data to be coded. Discrete approximate trigonometric expansions have previously been proposed for exploiting spatial correlation in 1D signals and images for the purpose of coding.In this paper, we apply the approximate trigonometric expansions to multispectral data, and explore their capability of spectral decorrelation across bands. We show that the compression algorithms employing approximate trigonometric expansions to multispectral imagery provide fast implementation and some how better spectral decorrelation efficiency than discrete cosine transform. For comparison purposes, the results are compared with the techniques employing the discrete cosine transform. Computer simulation results are presented.||URI:||http://ktisis.cut.ac.cy/handle/10488/7152||ISSN:||0277786X||DOI:||10.1117/12.280596||Rights:||© 1997 SPIE||Type:||Conference Papers|
|Appears in Collections:||Δημοσιεύσεις σε συνέδρια/Conference papers|
Show full item record
checked on Nov 20, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.