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题  目:  A New TV-Stokes Model for Image Deblurring and Denoising with Fast Algorithms


报告人:贾志刚  教授


摘  要: The famous TV-Stokes models, which improve the restored images comfortable,have been very successful in image denoising. In this talk, we propose a new TV-Stokes model for image deblurring with a good geometry explanation. In the tangential field smoothing, the data fidelity term is chosen to measure the distance between the solution and the orthogonal projection of the tangential field of the observation image onto the range of the conjugate of the blurry operator, while the total variation of the solution is chosen as the regularization

term. In the image reconstruction, we compute the smoothing part of the image from the smoothed tangential field for the first step, and use an anisotropic TV model to obtain the “texture” part of the deblurred image. The solvability properties for the minimization problems in two steps are established, and fast algorithms are presented. Numerical experiments demonstrate that the new deblurring model can capture the details of images

hidden in the blurry and noisy image, and the fast algorithms are efficient and robust.


时  间:2018年6月8日 下午3:30-5:30


地  点:教学楼411


报告人简介:贾志刚是江苏师范大学教授,博士毕业于华东师范大学,主要从事数值代数和图像处理研究,主持和参加多项国家自然科学基金面上项目。曾到英国曼彻斯特大学、香港浸会大学等高校进行学术访问与交流。在SIAM Matrix Anal.Appl.,BIT, J Sci. Comput.等国际知名期刊上发表学术论文20余篇。


邀请人: 陶敏 老师