Yiming Liu will present his research seminar/general exam on Thursday May 17 at 10AM in Room 402. The members of his committee are: Szymon Rusinkiewicz (advisor), Adam Finkelstein, and Kai Li. Everyone is invited to attend his talk, and those faculty wishing to remain for the oral exam following are welcome to do so. His abstract and reading list follow below. ----------------------- Single-shot Multispectral Imaging Multispectral imaging is a method to obtain the spectrum of each pixel in a 2D image. Instead of roughly aggregating light arriving at each pixel into one channel (e.g. gray-scale images) or three channels (RGB images), multispectral imaging divides the spectrum of each pixel into much narrower wavelength bands, obtaining a 3D cube of data indexed by spatial position and wavelength. Some prior works have shown promising acquisition quality, but they either require tedious manual work and very long acquisition time, or need active illumination or even additional cameras. Our work is a single-shot multispectral imaging method, which tries to capture a multispectral cube with one camera and within a single camera shot. A diffraction grating is put between camera lens and the scene to diffract lights from the scene into one clear zero-order image, and several dispersed first-order images. Each image is a projection of the 3D spectral cube on a plane. Based on these images and projections, and based on a prior assumption that camera noise is with a Poisson distribution, an maximum likelihood estimation algorithm is applied to infer the 3D spectral cube. Several synthetic and real experiments are designed to analyze the sensitivity of the acquisition quality with respect to calibration error and camera noise. ---------------------------- Reading list: Textbook: Szeliski, R. (2010). Computer vision: Algorithms and applications. Springer-Verlag New York Inc. Papers: 1. Cao, X., Du, H., Tong, X., Dai, Q.,& Lin, S. (2011). A Prism-Mask System for Multispectral Video Acquisition. IEEE transactions on pattern analysis and machine intelligence, 1-14. 2. Cao, X., Tong, X.,& Dai, Q. (2011). High resolution multispectral video capture with a hybrid camera system. CVPR. 3. Descour, M.,& Dereniak, E. (1995). Computed-tomography imaging spectrometer: experimental calibration and reconstruction results. Applied optics, 34(22), 4817-26. 4. Habel, R., Kudenov, M.,& Wimmer, M. (2012). Practical Spectral Photography. Eurographics (Vol. 31). 5. Hagen, N.,& Dereniak, E. L. (2008). Analysis of computed tomographic imaging spectrometers. I. Spatial and spectral resolution. Applied optics, 47(28), F85-95. 6. Mohan, A., Raskar, R.,& Tumblin, J. (2008). Agile Spectrum Imaging: Programmable Wavelength Modulation for Cameras and Projectors. Eurographics. 7. Schechner, Y. (2002). Generalized mosaicing: Wide field of view multispectral imaging. Pattern Analysis and Machine, 24(10), 1334-1348. 8. Brodzik, A. K.,& Mooney, J. M. (1999). Convex projections algorithm for restoration of limited-angle chromotomographic images. Journal of the Optical Society of America A, 16(2), 246.