Abstract
This paper presents Gabor-filtering-based probabilistic collaborative representation for hyperspectral image classification. Compared with the original collaborative representation classifier (CRC) and the CRC using Gabor features, the proposed classifier offers superior classification performance. The regularized versions of CRC using Gabor features have excellent classification performance; however, those classifiers have high computational cost. Experimental results show that the proposed approach can generate high classification accuracy with lower computational cost.
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