Abstract
The sparse representation based on over-complete dictionary is a new image representation theory.The redundancy of over-complete dictionary can enable it effectively to capture the geometrical characteristics of the images.In this paper,a novel detection method based on image sparse representation was introduced.The over-complete target dictionary is first constructed with atoms which are produced by two-dimensional Gaussian model.Then the sub-image blocks of the test image are extracted successively and the corresponding coefficients are calculated with the constructed over-complete target dictionary.There is a significant difference between the coefficients of objective and background.Whether the sub-image block contains small target or not can be determined by the index of sparse concentration.Experimental results demonstrated the effectiveness of the proposed method.
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