Title
Efficient algorithm for multispectral data coding using approximate trigonometric expansions
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.
Publication Date
12-1-1997
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Volume
3071
Number of Pages
191-202
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0031384494 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0031384494
STARS Citation
Memon, Qurban and Kasparis, Takis, "Efficient algorithm for multispectral data coding using approximate trigonometric expansions" (1997). Scopus Export 1990s. 3081.
https://stars.library.ucf.edu/scopus1990/3081