A Hierarchical Method Of Remotely Sensed Multispectral High Resolution Image Classification

H. Lin; D. Vidal-Madjar

doi:10.1117/12.941295

14 October 1987 A Hierarchical Method Of Remotely Sensed Multispectral High Resolution Image Classification

H. Lin, D. Vidal-Madjar

Proceedings Volume 0804, Advances in Image Processing; (1987) https://doi.org/10.1117/12.941295
Event: Fourth International Symposium on Optical and Optoelectronic Applied Sciences and Engineering, 1987, The Hague, Netherlands

Abstract

One of the simplest classification algorithm which utilizes a linear discriminant function is known as the minimum distance classifier, it is widely used in pattern recognition. But, it encounters the problem of useless dimension compensation when the feature dimensionality is very large. This is the situation when one wants to use textural features as input parameters for classification as it is now possible with the remotely sensed high resolution images (optical or radar). To avoid this problem, we propose a hierarchical classification algorithm.

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H. Lin and D. Vidal-Madjar "A Hierarchical Method Of Remotely Sensed Multispectral High Resolution Image Classification", Proc. SPIE 0804, Advances in Image Processing, (14 October 1987); https://doi.org/10.1117/12.941295

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