30 August 2013 Polarization image fast fusion method based on online dictionary learning
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Proceedings Volume 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications; 89100N (2013); doi: 10.1117/12.2032687
Event: ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, 2013, Beijing, China
Abstract
In this paper we propose a polarization image fast fusion approach based on online dictionary learning for sparse non-negative matrix factorization, aiming at improving the efficiency of fusion methods for polarization image based on non-negative matrix factorization. Firstly, all of the polarization parameter images are taken as source data sets for sparse non-negative matrix factorization using online dictionary learning algorithm, so as to extract three feature basis images. Then, after histogram matching, the three feature basis images are mapped into three color channels of IHS color space. Finally, the fused image is achieved via the transform from IHS to RGB color model. Experimental results show that, the proposed method not only has better capacity of color representation capability and effectively pop out detailed information of objects but enhances the running efficiency evidently as well.
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Guo-ming Xu, Mo-gen Xue, Guang-lin Yuan, Pu-cheng Zhou, "Polarization image fast fusion method based on online dictionary learning", Proc. SPIE 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications, 89100N (30 August 2013); doi: 10.1117/12.2032687; http://dx.doi.org/10.1117/12.2032687
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KEYWORDS
Image fusion

Polarization

Associative arrays

Image processing

Polarimetry

Camouflage

RGB color model

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