Blind Super-Resolution Reconstruction Algorithm under Affine Motion Model
ZHANG Xue-Song1, JIANG Jing2, PENG Si-Long3
1.Science and Technology on Electro-Optical Information Security Control Laboratory,No.53 Institute of China Electronics Technology Group Corporation,Sanhe 065201 2.School of Mechanicsal and Electronic Engineering,North China Institute of Science and Technology,Beijing 101601 3.The National Engineering Technology Research Center for ASIC Design,Institute of Automation, Chinese Academy of Sciences, Beijing 100190
Abstract An approach to the blind super-resolution (BSR) problem is proposed which yields a higher optical resolution image from a low-resolution (LR) image sequence with affine inter-frame motion. Firstly, an eigenvector-based method for constructing the null space of blurs is presented. It is used as the regularization constraint of the optimization procedure. Then, the iterative algorithm is developed for the triple-coupled problem. The proposed algorithm adopts a two-layer optimization strategy: in the first layer, the triple-coupled BSR problem is reduced to a quadratic form with respect to the blurs, and an nonlinear least squares (NLS) problem of the motion and the high-resolution (HR) image; in the second layer, the NLS problem is solved using a Gauss-Newton based method. The experimental results on synthetic data illustrate that the proposed BSR algorithm for affine transform, has better performance in terms of modeling the space-variant degradation process as well as restoring the local textures compared with the BSR algorithm for pure translation. Finally, the applicability of the proposed algorithm is demonstrated using real license plate images.
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2012, Vol. 25 
