ICA neural net to refine remote sensing with multiple labels

Harold H. Szu; James R. Buss

doi:10.1117/12.381669

5 April 2000 ICA neural net to refine remote sensing with multiple labels

Harold H. Szu, James R. Buss

Proceedings Volume 4056, Wavelet Applications VII; (2000) https://doi.org/10.1117/12.381669
Event: AeroSense 2000, 2000, Orlando, FL, United States

Abstract

We show how the unsupervised ANN modeling of image fusion of HVS can embody the mathematics of ICA to achieve blind source de-mixing of remote sensing images. We have shown when tow eyes are extended to multiple pixel has a large footprint on the ground. MLRS gives the percentage composition of ground radiation sources within the footprint and thus overcome the so-called 'boundary error' coined by Tucker in the Amazon deforestation over-estimation as follows.

Citation Download Citation

Harold H. Szu and James R. Buss "ICA neural net to refine remote sensing with multiple labels", Proc. SPIE 4056, Wavelet Applications VII, (5 April 2000); https://doi.org/10.1117/12.381669

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