Introductory Digital Image Processing: A Remote Sensing Perspective
Introductory Digital Image Processing: A Remote Sensing Perspective
Remote Sensing Digital Image Analysis: An Introduction
Remote Sensing Digital Image Analysis: An Introduction
Classification of Multispectral High-Resolution Satellite Imagery Using LIDAR Elevation Data
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
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Traditional classification algorithms are not suitable for feature extraction on high resolution satellite images, given the heterogeneity of the pixels of this type of imagery due to a great amount of detail. Most of this type of imagery is taken by the satellite in several bands and at different resolutions, and the method presented in this paper takes advantage of this situation, merging information provided by the multispectral bands with the panchromatic band. An Ikonos image of 2 × 2 km of the university campus of Alcala has been used for obtaining a classification with seven land use classes. A comparison is carried out between the traditional maximum likelihood method and the method developed here. The latter using context information obtained by the texture from the band with the maximum resolution, the panchromatic band. The results show how texture information improves maximum likelihood classification of the multispectral bands for smooth-textured classes.