Scene recovery: Combining visual enhancement and resolution improvement
数学专题报告
报告题目(Title)：Scene recovery: Combining visual enhancement and resolution improvement
报告人(Speaker)：曾铁勇
地点(Place)：后主楼1124
时间(Time)：9月8日 上午9：30-10：30
邀请人(Inviter)：段玉萍
报告摘要
Visibility enhancement of outdoor images under complex imaging conditions has been a crucial task for computer vision and received growing attention. However, existing image enhancement methods could result in typical block-like artifacts or color distortion. The undesirable impurities might also be significantly magnified after the enhancement task, further reducing the image quality. For enhancing and super-resolving complex real-world degradation, we propose a simultaneous visual enhancement and resolution improvement (VERI) variational scene recovery model for jointly enhancing image visibility and improving the resolution of the degraded image. Particularly, we estimate the scattering light map for degradation images to achieve clean scene radiance and simultaneously seek a high-quality image through a deep super-resolution network. The semi-proximal alternating direction method of multipliers (sPADMM) algorithm is employed for efficiently solving the minimization problems in the proposed model. Extensive experiments illustrate the effectiveness and robustness of the proposed method in dealing with various scenes, such as haze, sandstorm, underwater or low illumination.
主讲人简介
曾铁勇，2018年加入香港中文大学数学系, 现任香港中文大学终身正教授。自2020年起，他与同事一起创立了数学人工智能中心（CMAI），并担任CMAI主任。其主要研究方向为图像处理、优化、人工智能、科学计算、计算机视觉、机器学习和反问题。实验室近年来已在TPAMI、IJCV、IEEE TIP、TMI, TNNLS、CVPR、ICCV、SIAM等顶级期刊和会议上发表论文多篇，累计发表论文100余篇。有志于从事计算机视觉和机器学习研究的同学欢迎申请，主要研究方向为：自然图像处理、医学图像处理、图像复原、图像分割、目标检测、图像/视频压缩等。
