Signal Processing - September 2016 - 107

these analyses, readers may be inspired to design or develop
better sampling schemes for multispectral sensing.

Acknowledgments
We would like to thank Weisheng Dong and Lizhi Wang for
their helpful discussions and Linsen Chen, Weixin Zhu, and
Hao Zhu for their assistance on implementation and experimentation. We also would like to acknowledge funding from
NSFC Project numbers 61422107, 61327902, 61371166, and
61120106003.

Authors
Xun Cao (caoxun@nju.edu.cn) received his B.S. degree
from Nanjing University, China, in 2006 and his Ph.D.
degree from the Department of Automation, Tsinghua
University, Beijing, China, in 2012. He is currently an associate professor at the School of Electronic Science and
Engineering, Nanjing University, China. He was a visiting
researcher at Philips Research, Aachen, Germany, in 2008
and Microsoft Research Asia, Beijing, China, during 2009-
2010. He was a visiting scholar at the University of Texas at
Austin, Texas, from 2010 to 2011. His research interests
include computational photography, image-based modeling,
and rendering.
Tao Yue (yuetao@nju.edu.cn) received the B.S. degree in
automation from Northwestern Polytechnical University,
Xi'an, China, in 2009 and the Ph.D. degree from Tsinghua
University, Beijing, China, in 2015. He is currently an associate researcher with the School of Electronic Science and
Engineering, Nanjing University, China. His research interests
mainly include computer vision, image processing, and computational photography.
Xing Lin (xinglin@stanford.edu) received the B.E. degree
in electronic science and technology from Xidian University,
Xi'an, China, in 2010 and the Ph.D. degree in automation
from Tsinghua University, Beijing, China, in 2015. He is a
research associate with the Howard Hughes Medical Institute
at the Department of Biology, Stanford University, California.
His research interests include computational imaging, computer vision, and optical bioimaging.
Stephen Lin (stevelin@microsoft.com) received the
B.S.E. degree from Princeton University, New Jersey, and
the Ph.D. degree from the University of Michigan, Ann
Arbor. He is currently a senior researcher with the Internet
Graphics Group of Microsoft Research, Beijing, China. His
current research interests include computer vision, image
processing, and computer graphics. He served as a program
cochair for the International Conference on Computer Vision
2011 and the Pacific-Rim Symposium on Image and Video
Technology 2009.
Xin Yuan (x.yuan@alcatel-lucent.com) is currently a video
analysis and coding lead researcher at Bell Labs, Murray Hill,
New Jersey. He had previosuly been a postdoctoral associate
with the Department of Electrical and Computer Engineering,
Duke University, from 2012 to 2015, where he was working on
compressive sensing and machine learning. Before joining

Duke, he obtained his B.Eng. and M.Eng. degrees from Xidian
University, Xi'an, China, in 2007 and 2009, respectively, and
his Ph.D. degree from the Hong Kong Polytechnic University
in 2012. His research interests are in signal processing, computational imaging, and machine learning.
Qionghai Dai (qionghaidai@tsinghua.edu.cn) received his
Ph.D. degree in automation from Northeastern University,
Shenyang, China, in 1996. He has been a faculty member
since 1997 and a professor since 2005 of the Department of
Automation, Tsinghua University, Beijing, China. He has published more than 120 conference and journal papers, and he
holds 67 patents. His current research interests include the
areas of computational photography, computational optical
sensing, and compressed sensing imaging and vision. His
work is motivated by challenging applications in the fields of
computer vision, computer graphics, and robotics.
Lawrence Carin (lcarin@duke.edu) received his B.S.,
M.S., and Ph.D. degrees in electrical engineering from the
University of Maryland, College Park, in 1985, 1986, and
1989, respectively. In 1989, he joined the Department of
Electrical Engineering at Polytechnic University, Brooklyn,
New York, as an assistant professor, where he became an associate professor in 1994. In 1995, he joined the Department of
Electrical and Computer Engineering, Duke University,
Durham, North Carolina, where he is currently a professor. He
was the chair of the Department of Electrical Communication
Engineering from 2011 to 2014. Since 2014, he has been the
vice provost of research at Duke University. His current
research interests include machine learning and statistics. He is
a Fellow of the IEEE.
David J. Brady (dbrady@duke.edu) is a professor of electrical and computer engineering at Duke University and Duke
Kunshan University. He is a graduate of Macalester College
and Caltech and was previously on the faculty of the
University of Illinois. He is the author of Optical Imaging and
Spectroscopy. His research focuses on array cameras and
compressive tomography. He is a Fellow of IEEE, OSA, and
SPIE, and he won the 2013 SPIE Dennis Gabor Award for
work on compressive holography.

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