A VQ-Based Parameter Identification Approach to Blind Image
Restoration and Resolution Enhancement
Qiao Jian-ping①②; Liu Ju①; Yan Hua①; Sun Jian-de①
①School of Information Science and Engineering, Shandong University, Jinan 250100, China; ②National Laboratory on Machine Perception, Beijing University, Beijing 100871, China
Abstract：Blur identification is usually necessary in image recovery. In this paper, an improved approach is proposed on the basis of VQ-based blur identification algorithm developed by Nakagaki, In this method, Sobel operator is used for extracting feature vectors, so that the selection of the parameter of the LOG filter is avoided and this method is robust to different types of images. The dimensionality of the vector is reduced by utilizing DCT. Meantime, extension of this method to blind super-resolution image restoration is achieved. After blur identification, a super-resolution image is reconstructed from several low-resolution images obtained by different foci. Simulation results demonstrate the feasibility and validity of the method.
2006, Vol. 28 
