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Although sparse coding has emerged as an extremely powerful tool for texture and image classification, it neglects the relationship of coding coefficients from the same class in the training stage, which may cause a decline in the classification performance. In this paper, we propose a novel coding strategy named compact sparse coding for groundbased cloud classification. We add a constraint on coding coefficients into the objective function of traditional sparse coding. In this way, codingdoi:10.1587/transinf.2015edl8095 fatcat:iva2gd7dvvbhbpkm6f3ma56noy