Efficient Blind Image Restoration Based on 1-D Generalized Cross Validation
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Generalised finite radon transform for N x N images
Image and Vision Computing
Reply to "Comments on 'The discrete periodic radon transform'"
IEEE Transactions on Signal Processing
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Isotropic blur identification for fully digital auto-focusing
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
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Restoring an image from its convolution with an unknown blur function is a well-known ill-posed problem in image processing. Many approaches have been proposed to solve the problem and they have shown to have good performance in identifying the blur function and restoring the original image. However, in actual implementation, various problems incurred due to the large data size and long computational time of these approaches are undesirable even with the current computing machines. In this paper, an efficient algorithm is proposed for blind image restoration based on the discrete periodic Radon transform (DPRT). With DPRT, the original two-dimensional blind image restoration problem is converted into one-dimensional ones, which greatly reduces the memory size and computational time required. Experimental results show that the resulting approach is faster in almost an order of magnitude as compared with the traditional approach, while the quality of the restored image is similar.