30 December 1994 Three-dimensional signal analysis of remotely sensed data
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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.
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Daniela Coltuc, Daniela Coltuc, Klaus Seidel, Klaus Seidel, Mihai P. Datcu, Mihai P. Datcu, } "Three-dimensional signal analysis of remotely sensed data", Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); doi: 10.1117/12.196724; https://doi.org/10.1117/12.196724

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