A Neural Network Method of Selective Endmember for Pixel Unmixing
نویسنده
چکیده
Remote sensing images contain a lot of mixed image pixels, but it is difficult to classify these pixels. If the number of pixel’s end-member is regarded as unchangeable, the traditional pixel unmixing algorithm cannot get a good result. In this paper we develop a new method of selective end-members for pixel unmixing based on the fuzzy ARTMAP neural network, which firstly compares the pixel’s spectral to the conference one and then gets the number of end-member. When it is taken into account, we use an ARTMAP neural network to extract subpixel information. Finally, experimental results show that the selective end-member algorithm achieves improvement over conventional ANN algorithms and conventional linear algorithms.
منابع مشابه
new approach Automatic neuro - hyperspectral unmixing : a
and efficient solution to the unmixing problem. independence great discrimination ability on unlike signatures, giving a robust The model has great noise robustness, a correlation rate and endmember number always low Error Ratios for all cases. components, endmember number and proportion on the mixture, providing network behaviour vs. the Signal-to-Noise Ratio, correlation rate between order to...
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