报告题目: Blind Image Deblurring: Past, Current and Future

报告人：曾铁勇 教授 香港中文大学

邀请人：王卫卫教授

报告时间：2022年5月26日10:00-11:30

腾讯会议：613-806-607

报告人简历：曾铁勇博士，教授，香港中文大学数学人工智能中心主任，科技部重点专项首席科学家，2021年香港数学会青年学者奖获得者。于2000年本科毕业于北京大学，2007年巴黎第十三大学获得博士学位。主要研究领域包括数据科学，优化理论，图像处理，反问题等。在优化、图像处理、反问题的国际一流杂志SIAM Journal on Imaging Sciences, SIAM Journal on Scientific Computing, International Journal of Computer Vision, Journal of Scientific Computing，IEEE PAMI, IEEE TNNLS, IEEE Transactions on Image Processing，Pattern Recognition，Journal of Mathematical Imaging and Vision等发表过百篇SCI论文。

Abstract: Blind image deblurring is a challenging task in imaging science where we need to estimate the latent image and blur kernel simultaneously. To get a stable and reasonable deblurred image, proper prior knowledge of the latent image and the blur kernel is urgently required. In this talk, we address several of our recent attempts related to image deblurring. Indeed, different from the recent works on the statistical observations of the difference between the blurred image and the clean one, we first report the surface-aware strategy arising from the intrinsic geometrical consideration. This approach facilitates the blur kernel estimation due to the preserved sharp edges in the intermediate latent image. Extensive experiments demonstrate that our method outperforms the state-of-the-art methods on deblurring the text and natural images. Moreover, we discuss the Quaternion-based method for color image restoration. After that, we extend the quaternion approach for blind image deblurring and discuss the pixel screening correction method.