Compressive sensing reconstruction based on weighted directional total variation |
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Authors: | Lihua Min Can Feng |
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Institution: | 1.School of Science,Nanjing University of Posts and Telecommunications,Nanjing,China;2.Department of Beidou,North Information Control Research Academy Group Co., Ltd.,Nanjing,China |
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Abstract: | Directionality of image plays a very important role in human visual system and it is important prior information of image. In this paper we propose a weighted directional total variation model to reconstruct image from its finite number of noisy compressive samples. A novel self-adaption, texture preservation method is designed to select the weight. Inspired by majorization-minimization scheme, we develop an efficient algorithm to seek the optimal solution of the proposed model by minimizing a sequence of quadratic surrogate penalties. The numerical examples are performed to compare its performance with four state-of-the-art algorithms. Experimental results clearly show that our method has better reconstruction accuracy on texture images than the existing scheme. |
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