Acta Optica Sinica, Volume. 29, Issue 11, 3025(2009)
A Total-Variation Majorization-Minimization Sectioned Restoration Algorithm with Gradient Ringing Metric Image Quality Assessment
For eliminating the ringing artifacts between the sub-frames of the sectioned restoration algorithm for images with space-variant point spread function (SVPSF),the paper introduces a sectioned restoration algorithm,which bases on total variation(TV) majorization-minimization restoration algorithm and gradient ringing metric (GRM) image quality assessment approach.Firstly,the SVPSF-blurred image is divided into rectangular sections,circular sections or any other,which relies on the distribution of the degradation function,with some overlapped-regions.Then,each sub-section is restored by TV restoration algorithm with GRM as the convergence limit of restoration iteration.The GRM method is helpful to identify ringing of restored image,which relies on the similarity of the gradients of two images.After removing the overlapped regions,the sub-frames are spliced together to construct the composite full image.Taking the restorations of the rectangular-section and circular-section SVPSF-blurred images as examples,the paper proves that the algorithm is good at suppressing ringing artifacts.Consequently a better image with smooth splicing is obtained.The drawback of the sectioned restoration algorithm is overcomed.
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Tao Xiaoping, Feng Huajun, Zhao Jufeng, Li Qi, Xu Zhihai. A Total-Variation Majorization-Minimization Sectioned Restoration Algorithm with Gradient Ringing Metric Image Quality Assessment[J]. Acta Optica Sinica, 2009, 29(11): 3025
Category: Image Processing
Received: Dec. 11, 2008
Accepted: --
Published Online: Nov. 16, 2009
The Author Email: Xiaoping Tao (taoxp99@gmail.com)