小波系数插值支持下的遥感影像混合像元分解

doi:10.3969/j.issn.0255-8297.2012.06.009

Abstract

Abstract: This paper proposes a wavelet coefficient interpolation method, which uses the neighboring information in the spatial domain for spectral unmixing of remote sensing images. A super-resolution image is first generated using bilinear interpolation of wavelet coefficients. The new image is then classified to derive
a super-resolution classification map. Finally, an abundance map at the original spatial resolution is obtained using a counting window on the super-resolution classification map. This way, the original image is unmixed. A simulated TM image of Guangzhou City is used to verify the proposed method. It is found that the method performs best among three methods as it can make use of neighboring information in the space to improve unmixing accuracy.

Key words: remote sensing, mixed pixel, wavelet transformation, super resolution reconstruction, bilinear interpolation

CLC Number:

P751.1

LI Xi1, CHEN Feng-rui2, YU Zhi-feng1,3. Spectral Unmixing of Remote Sensing Images Using Interpolation of Wavelet Coefficients[J]. Journal of Applied Sciences, 2012, 30(6): 613-618.

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Spectral Unmixing of Remote Sensing Images Using Interpolation of Wavelet Coefficients

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