Systolic S.o.m. Neural Network for Hyperspectral Image Classification
نویسندگان
چکیده
Hyperspectral image sensor developments on the study of the Earth's surface give way to images with higher spectral and spatial resolutions. In fact, the higher the resolution, the greater the size of these images. The use of these sensors by space-borne satellite systems will provide an enormous and continuous flow of data with constraints placed on onboard storage, and data transmission bandwidth. New algorithms and computer capabilities will be necessary for the classification, compression and preprocessing of these images. In this chapter, we propose an SOM algorithm for hyperspectral classification implemented by one systolic array, to provide real-time hyperspectral compression facilities.
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