报告人：武筱林教授 （Prof. Wu Xiaolin）
时 间：2011年5月27日下午15:00 – 16:30
地 点：武汉光电国家实验室（筹）A101
报告人简介：
Professor Wu Xiaolin 武筱林教授
Department of Electrical & Computer Engineering 电子与计算机工程系
McMaster University 麦克马斯特大学
武筱林教授于1982年在武汉大学获得计算机科学学士学位，1988年在加拿大卡尔加里大学获得计算机科学博士学位。武教授从1988年开始他的学术生涯，此间他曾在西安大略大学（加拿大）、纽约科技大学（美国）任教。现为麦克马斯特大学（加拿大）电子与计算机工程系教授，同时也是NSERC-DALSA 数字影院首席科学家。他的研究领域包括多媒体信号压缩，联合信源与信道编码，多重描述编码，网络自适应可视通信和图像处理。武教授在上述领域已经发表了超过200篇学术论文并拥有两项专利，与此同时他还是IEEE Fellow，IEEE图像处理汇刊副主编，IEEE多媒体汇刊副主编，IEEE图像处理、多媒体、数据压缩和信息理论领域的众多国际会议和研讨会技术委员会成员。
Biography:
Xiaolin Wu got his B.Sc. from Wuhan University, China in 1982, and Ph.D. from University of Calgary, Canada in 1988, both in computer science. Dr. Wu started his academic career in 1988, and has since been on the faculty of University of Western Ontario, New York Polytechnic University, and currently McMaster University, where he is a professor at the Department of Electrical & Computer Engineering and holds the NSERC-DALSA Industrial Research Chair in Digital Cinema. His research interests include multimedia signal compression, joint source-channel coding, multiple description coding, network-aware visual communication and image processing. He has published over two hundred research papers and holds two patents in these fields. Dr. Wu is an IEEE fellow, and an associated editor of IEEE Transactions on Image Processing. He also served as an associated editor of IEEE Transactions on Multimedia and on the technical committees of many IEEE international conferences/workshops on image processing, multimedia, data compression, and information theory.
报告摘要：
得益于对图像技术多年的深入研究和持续投入，数字图像在空间、频域和时域的保真度一直稳步提升，现在已经可以赶上甚至超过传统胶卷。但是无论传感技术如何发展，总会有一些令人兴奋的新应用要求更高的图像精度。医药、空间、工程和科学领域的研究人员总是渴望得到更小尺度、更精确的图像细节。由于传感器件自身的保真能力受到物理定律的严格限制，所以用户不能指望仅仅靠传感器本身达到这些成像要求。而通过信号处理技术从算法上提高传感器件的成像精度已经并且将会在图像/视频处理和机器视觉领域扮演重要的角色。在本次报告中将会涉及高保真图像/视频处理领域的一些技术难题，并回顾已经存在的和正在兴起的解决这些难题的科学方法和技术手段。
Abstract:
Through years of intensive research and heavy investment in imaging technologies, spatial, spectral and temporal fidelities of digital images are steadily improving and now can match and even exceed those of traditional film. However, no matter how much sensor technologies advance, new, more exciting and exotic applications will always present themselves that demand even higher image precision. Researchers in medicine, space, engineering and sciences all have insatiable desire for imaging ever more minuscule and subtle details. Users cannot solely count on raw sensor capability to satisfy their needs. There exist hard physical limits on native fidelity of imaging devices. Therefore, signal processing techniques to algorithmically improve native sensor precision are and will be playing an important role in the fields of image/video processing and computer vision. In this talk, we will examine challenging technical problems in the field of high-fidelity image/video processing, and review scientific and engineering approaches, both established and emerging, to overcoming these technical challenges.
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