Abstract:  Super-resolution image reconstruction has important application value in various fields and has broad application prospects. It is an ill-posed problem to reconstruct the high-resolution image from the low-resolution image. The most effective method is to add the regularization term to solve it. This paper adds the fractional order total variation (FOTV) as the regularization term constraint solution space based on the traditional total variation (TV), and uses the texture detection function to determine the local features at different locations in the image, and selects the adaptive order. The alternating direction multiplier algorithm is used to divide the optimization function into multiple sub-problems and reduce the complexity of the operation. In this paper, the bi-regularization constraints of TV and the adaptive FOTV are used to adaptively reconstruct the texture detail information while removing the noise and sharpening edge. Experimental results show that compared with other methods, the proposed method improves the quality of image reconstruction, and both the PSNR and SSIM values are improved.

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