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Proceedings Paper

Three-dimensional signal analysis of remotely sensed data
Author(s): Daniela Coltuc; Klaus Seidel; Mihai P. Datcu
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Paper Abstract

The paper presents a method for the simultaneous analysis of a collection of satellite images derived from different sources. The images are multispectral, multisensor, multitemporal and synthetically generated images. All these images must have the same dimension, the same resolution, and they must refer to the same geographical area. The images are organized in a parallel structure that form a 3-D block of data. We analyze this 3-D block of data using the 3- D sliding window Fourier transform (SWFT) applied on volumes of size 8 X 8 X 8. The reasons for using this strategy are: (1) the SWFT is a technique which leads to good results in 1-D signals processing like vocal signals. (2) Measurements of the receptive fields of simple cells in visual cortex having shown them to be like Gaussian modulated sinusoids. (3) The transform on the third dimension does the fusion of the different types of data included in the original multimodal image. After the computation of the 3-D transformed images we used a clustering procedure in order to reduce the dimensionality of the transformed data. To achieve a great flexibility in the selection of the significant images a slightly modified k means algorithm was used.

Paper Details

Date Published: 30 December 1994
PDF: 5 pages
Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); doi: 10.1117/12.196724
Show Author Affiliations
Daniela Coltuc, Univ. Politehnica (Romania)
Klaus Seidel, Swiss Federal Institute of Technology (Switzerland)
Mihai P. Datcu, Deutsche Forschungs- und Versuchsanstalt fuer Luft- und Raumfahrt eV (Germany)


Published in SPIE Proceedings Vol. 2315:
Image and Signal Processing for Remote Sensing
Jacky Desachy, Editor(s)

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