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16 June 1995 Parallel cooperative segmentation method for multispectral images
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Abstract
The paper focuses on the problem of the mulitspectral image segmentation. A multispectral image is composed by several monospectral images (black and white for example), constituted by different wavelength bands. Consequently, the complementarity and/or redundancy of data, through data fusion, makes reliable and robust military or individual systems. The parallelism of the algorithm is inherent: different monospectral images may be sometimes processed in parallel without information exchanges or synchronization, or different monospectral images may be processed in parallel, but with explicit information exchanges and synchronization. This method is a new approach of image data fusion. It does not enter the taxinomy of image data fusion methods, because its level of fusion is between two classical levels. The image data fusion is performed while segmenting together the different images. The image data fusion is treated as an extension of segmentation methods. The classical or monospectral image features edges and regions that have been extended to the multispectral framework. Their attributes gather the information coming from all spectral images.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Patrick J. Bonnin, Cyril Maurette, Brigitte Hoeltzener-Douarin, and Edwige E. Pissaloux "Parallel cooperative segmentation method for multispectral images", Proc. SPIE 2488, Visual Information Processing IV, (16 June 1995); https://doi.org/10.1117/12.211977
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