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In order to enhance the performance of image recognition, a sparsityaugmented probabilistic collaborative representation based classification(SA-ProCRC) method is presented. The proposed method obtains the densecoefficient through ProCRC, then augments the dense coefficient with a sparseone, and the sparse coefficient is attained by the orthogonal matching pursuit(OMP) algorithm. In contrast to conventional methods which require explicitcomputation of the reconstruction residuals for each class, the proposed methodemploys the augmented coefficient and the label matrix of the training samplesto classify the test sample. Experimental results indicate that the proposedmethod can achieve promising results for face and scene images. The source codeof our proposed SA-ProCRC is accessible athttps://github.com/yinhefeng/SAProCRC.

A sparsity augmented probabilistic collaborative representation based classification method