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Acquisition and Analysis of Giga-pixel spectral information

Acquisition and Analysis of Giga-pixel spectral information. IJARC CORE6 Project 11 th Jan. 2010 Rei Kawakami. Imaging devices. Cameras are everywhere, but …. Limited to RGB or Monochrome images. Spectral Imaging Devices. LCTF filter 35,000 $. Hyper-spectral camera 55,000 $.

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Acquisition and Analysis of Giga-pixel spectral information

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  1. Acquisition and Analysis ofGiga-pixel spectral information IJARC CORE6 Project 11th Jan. 2010 Rei Kawakami

  2. Imaging devices Cameras are everywhere, but … • Limited to RGB or Monochrome images

  3. Spectral Imaging Devices LCTF filter 35,000 $ Hyper-spectral camera 55,000 $ Line spectral scanner 25,000 $ • High cost • Limited resolution • Few softwares available

  4. Proposal • Giga-pix hyperspectral imaging system • High resolution (Giga-pix order) • Off-the-shelf (~ 1,000 $) • Software to analyze high-res hyper-spectral data

  5. Why do we need it? • Why spectra? • Pure physical quantity • Represents precise object’s optical property • Sensor independent • Why high-resolution? • Spectrum at microscopic level of details • Material analysis • Preservation

  6. Possible applications • E-heritage • Preservation of precise color • Medical imaging • Analysis of skins, neurons, blood, etc. • Material analysis / biological analysis • Semiconductors • Fossils • Micro-organisms • Birds, insects

  7. Outcomes • Imaging system • Software to analyze data

  8. Proposed Imaging system Large-format lens CCD Spectral transmittance varies linearly Giga-pixel Camera @ Microsoft research M. Ezra et al.

  9. Linear Variable Filter Monochrome camera Filter Rotational/translational stage

  10. Advantages • Giga-pixel spectral information • Microscopic level • Efficient combination • Translational motion • Low cost • Cost of the filter: ~ 1,000 $ • FWHF: ~ 4 nm to 8 nm • Transmittance: ~ 30 to 40 %

  11. Technical Issues • Stitching • Filter causes intensity change • Low intensity vs. Acquisition time • Denoising • Data compression • Wavelength ~ 80 dimension • Efficient data-acquisition • Size of the filter = bottleneck CCD Filter Useless

  12. Methods for Visualization & Analysis • Visualization • Development of GUI for user assistance • Analysis • Material estimation (spectral unmixing) • Illumination/Surface reflectance separation • Segmentation

  13. Survey on related cameras Schedule Development of the camera Writing a paper Survey on spectral analysis Developing a new spectral analysis method Experiments with the sensor and the method Writing a paper Presenting a paper about the sensor Discussions with collaborators

  14. How to check Progress • Number of meetings • with collaborators • Number of days • I spend at Microsoft research • Number of papers • 2

  15. Budget

  16. Microsoft tools & techniques • Giga-pixel camera • Visual studio • Office Live Meeting • Collaboration with Microsoft researchers

  17. My research experience • PHD candidate @ University of Tokyo, 05-08 • Surface color estimation • ICCV 2005, JOSA 2007, CVPR 2009 • Surface reflectance/illumination separation • Project researcher @ University of Tokyo, 08- • Shadow removal • VRST 2008 • Optical property estimation of layered surfaces • MIRU 2009 (oral presentation, in Japanese)

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