Prof.Xiaolin Wu学术报告
题目：Augmented Perception of High Dynamic Range Images via Optimal Tone
Mapping
报告人：Prof.Xiaolin Wu
Department of Electrical and Computer Engineering, McMaster University
School of Electronic Information and Electrical Engineering, Shanghai Jiao
Tong University
时间：5月22（周四）上午10：00--11：00
地点：西区电三楼314会议室
主办单位：信息学院 电子工程与信息科学系
多媒体计算与通信教育部-微软重点实验室
摘要：
The human visual system (HVS) has a quite limited power in discriminating
different light intensity levels. According to DICOM, the medical image
standard, under ideal viewing conditions, radiologists can only distinguish
up to 465 levels of gray. On the other hand, modern image acquisition
devices can generate digital images of intensity resolution that easily
exceeds 10 bits (1024). The intensity resolution of modern optoelectronic
displays can reach 10 bits as well. Therefore, there exists a substantial
gap between the achievable precision of devices and the discrimination
capability of HVS in pixel amplitude. This gap presents a serious obstacle
in applications where images of high dynamic range (HDR) are scrutinized and
acted upon ultimately by human viewers; for instance, in medical imaging it
is the radiologist not a computer that makes diagnostics and clinic
decisions relying primarily on his/her visual examination of the input HDR
image.
Tone mapping is required to display HDR images. Its objective is to augment
human vision, so viewers can see details that are otherwise discernible to
naked eyes. As tone mapping is a process of compressing the intensity
dynamic range, it inevitably causes loss or/and distortion of information.
The problem exists even for professional-grade HDR displays for the simple
reason that the amplitude quantization precision of pixels exceeds the raw
discrimination power of HVS. Therefore, the challenge of HDR tone mapping
is how to make as much wanted information conspicuous as possible while
preventing or minimizing information loss and/or visual artifacts.
We cast the problem into a framework of constrained optimization and propose
a linear program algorithm to solve it. Our approach represents a
fundamental departure from the existing ad hoc HDR tone mapping techniques;
it improves perceptual quality of displayed HDR images without artifacts of
HDR compression (e.g., double edging, halos, embossment, etc.).
简介：
Xiaolin Wu, B.Sc., Wuhan University, 1982; Ph.D., University of Calgary,
Canada, 1988. Dr. Wu started his academic career in 1988, and has since
been on the faculty of University of Western Ontario, New York Polytechnic
University (NYU-Poly), and currently McMaster University, where he is a
professor at the Department of Electrical & Computer Engineering. His
research interests include image processing, multimedia signal coding and
communication, joint source-channel coding, multiple description coding, and
network-aware visual communication. He has published over two hundred
research papers and holds three patents in these fields. Dr. Wu is an IEEE
fellow, past associated editors of IEEE Transactions on Image Processing and
on Multimedia, a member of the IEEE Industrial DSP standing committee, and
recipient of numerous international awards and honors, including NSERC
senior industrial research chair, Velux Fellowship, Nokia Research
Fellowship, Monsteds Fellowship, McMaster Distinguished Engineering
Professor, UWO Distinguished Research Professorship, and the 2008 VCIP best
paper award.
非常欢迎全校感兴趣师生参加！
Mapping
报告人：Prof.Xiaolin Wu
Department of Electrical and Computer Engineering, McMaster University
School of Electronic Information and Electrical Engineering, Shanghai Jiao
Tong University
时间：5月22（周四）上午10：00--11：00
地点：西区电三楼314会议室
主办单位：信息学院 电子工程与信息科学系
多媒体计算与通信教育部-微软重点实验室
摘要：
The human visual system (HVS) has a quite limited power in discriminating
different light intensity levels. According to DICOM, the medical image
standard, under ideal viewing conditions, radiologists can only distinguish
up to 465 levels of gray. On the other hand, modern image acquisition
devices can generate digital images of intensity resolution that easily
exceeds 10 bits (1024). The intensity resolution of modern optoelectronic
displays can reach 10 bits as well. Therefore, there exists a substantial
gap between the achievable precision of devices and the discrimination
capability of HVS in pixel amplitude. This gap presents a serious obstacle
in applications where images of high dynamic range (HDR) are scrutinized and
acted upon ultimately by human viewers; for instance, in medical imaging it
is the radiologist not a computer that makes diagnostics and clinic
decisions relying primarily on his/her visual examination of the input HDR
image.
Tone mapping is required to display HDR images. Its objective is to augment
human vision, so viewers can see details that are otherwise discernible to
naked eyes. As tone mapping is a process of compressing the intensity
dynamic range, it inevitably causes loss or/and distortion of information.
The problem exists even for professional-grade HDR displays for the simple
reason that the amplitude quantization precision of pixels exceeds the raw
discrimination power of HVS. Therefore, the challenge of HDR tone mapping
is how to make as much wanted information conspicuous as possible while
preventing or minimizing information loss and/or visual artifacts.
We cast the problem into a framework of constrained optimization and propose
a linear program algorithm to solve it. Our approach represents a
fundamental departure from the existing ad hoc HDR tone mapping techniques;
it improves perceptual quality of displayed HDR images without artifacts of
HDR compression (e.g., double edging, halos, embossment, etc.).
简介：
Xiaolin Wu, B.Sc., Wuhan University, 1982; Ph.D., University of Calgary,
Canada, 1988. Dr. Wu started his academic career in 1988, and has since
been on the faculty of University of Western Ontario, New York Polytechnic
University (NYU-Poly), and currently McMaster University, where he is a
professor at the Department of Electrical & Computer Engineering. His
research interests include image processing, multimedia signal coding and
communication, joint source-channel coding, multiple description coding, and
network-aware visual communication. He has published over two hundred
research papers and holds three patents in these fields. Dr. Wu is an IEEE
fellow, past associated editors of IEEE Transactions on Image Processing and
on Multimedia, a member of the IEEE Industrial DSP standing committee, and
recipient of numerous international awards and honors, including NSERC
senior industrial research chair, Velux Fellowship, Nokia Research
Fellowship, Monsteds Fellowship, McMaster Distinguished Engineering
Professor, UWO Distinguished Research Professorship, and the 2008 VCIP best
paper award.
非常欢迎全校感兴趣师生参加！
