Title :
Multispectral image fusion using local mapping techniques
Author :
Scheunders, Paul
Author_Institution :
Vision Lab., Antwerp Univ., Belgium
Abstract :
In this paper, fusion of multispectral images for visualization is aimed at, based on the projection of the scatter-diagrams onto a one-dimensional space. Linear as well as nonlinear projection techniques are used. In contrast with existing mapping techniques which work globally, a local mapping technique is constructed. In this technique, the images are subdivided into blocks, where each block of pixels is visualized through a different map. Then, for each pixel, a locally adapted map is created by weighting the maps of the surrounding blocks using Euclidean distance measure. A linear local mapping, based on local PCA and a nonlinear local mapping, based on Kohonen´s SOM map are generated and compared to the global procedures. Experiments are conducted on multispectral LANDSAT imagery
Keywords :
data visualisation; image processing; principal component analysis; self-organising feature maps; sensor fusion; 1D space; Euclidean distance measure; Kohonen SOM map; image subdivision; linear local mapping; linear projection techniques; local PCA; local mapping techniques; multispectral LANDSAT imagery; multispectral image fusion; nonlinear local mapping; nonlinear projection techniques; scatter-diagrams; visualization; Biomedical imaging; Euclidean distance; Humans; Image segmentation; Multispectral imaging; Principal component analysis; Remote sensing; Satellites; Scattering; Visualization;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.906075