TUT-3: The Color Imaging Pipeline for Digital Still and Video Cameras

Date: Sunday Morning, October 12

Presented by

Keigo Hirakawa, Harvard University, Patrick J. Wolfe Harvard University, and Truong Nguyen University of California, San Diego


The ubiquity of digital color image content continues to raise consumer technological awareness and expectations, and places a greater demand than ever on algorithms that support color image acquisition and the engineers that design them. In this tutorial we address key technical challenges to imaging pipeline design presented by demands such as shrinking device footprints, increasing throughput, and enhancing color fidelity. This topic is of broad interest yet sufficiently focused to provide a clear, structured framework for the tutorial setting. Its aim is to educate students, researchers, and industry practitioners about current and future trends in the color image processing pipeline, brought about by changes in hardware, signal processing, and marketplace demands. Participants will gain an understanding of practical implementational trade-offs, along with a set of technical tools and frameworks for thinking holistically about the color image processing pipeline for still and video cameras.


Speaker Biographies

Keigo Hirakawa is currently with the School of Engineering and Applied Sciences and Department of Statistics at Harvard, where he co-leads a collaboration with Sony Electronics to address future challenges in the image processing pipeline. He has previously been an ASIC engineer and principal image scientist for the camera division of Hewlett-Packard/Agilent Technologies, and his past and current collaborations with camera manufacturers include Sony, Micron, Texas Instruments, NEC, and Kodak. He is the co-inventor (with Prof. T. W. Parks) of the AHD demosaicking algorithm (2003), which is by now the standard for most open-source raw image converters. His research focuses on statistical signal processing, color imaging, and computer vision.

Patrick J. Wolfe directs the Statistics and Information Sciences Laboratory at Harvard, which he founded in 2004 after holding a fellowship and college lectureship in engineering and computer science at the University of Cambridge. Prof. Wolfe has received honors from the International Society for Bayesian Analysis, the Acoustical Society of America, and the IEEE for his work in statistical sound and image processing, including (jointly with Dr. Hirakawa) a DoCoMo innovative paper award (ICIP 2007) for work in color filter array design. His lab's research is supported by NSF, DARPA, MIT Lincoln Laboratory, and Sony, and focuses on statistical signal processing and its application to tasks involving modern high-dimensional data sets, in particular sounds, images, and networks.

Truong Q. Nguyen is currently a Professor at the University of California, San Diego, Department of Electrical Engineering. His research interests are video processing algorithms and their efficient implementation. He is the coauthor of the popular textbook "Wavelets & Filter Banks" (with Prof. Gilbert Strang, Wellesley-Cambridge Press, 1997). A Fellow of the IEEE and recipient of the IEEE Transaction in Signal Processing Paper Award (Image and Multidimensional Processing area) for the paper he co-wrote with Prof. P. P. Vaidyanathan on linear-phase perfect-reconstruction filter banks (1992), he is the author of over 200 publications as well as several Matlab-based toolboxes on image compression, electrocardiogram compression, and filter bank design.