acquisition and analysis of giga-pixel spectral information
DESCRIPTION
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 $. - PowerPoint PPT PresentationTRANSCRIPT
ACQUISITION AND ANALYSIS OF
GIGA-PIXEL SPECTRAL
INFORMATION
IJARC CORE6 Project
11th Jan. 2010
Rei Kawakami
IMAGING DEVICES
• Limited to RGB or Monochrome images
Cameras are everywhere, but …
SPECTRAL IMAGING DEVICES
LCTF filter35,000 $
Hyper-spectral camera55,000 $
Line spectral scanner25,000 $
• High cost• Limited resolution• Few softwares available
PROPOSAL Giga-pix hyperspectral imaging system
High resolution (Giga-pix order)Off-the-shelf (~ 1,000 $)
Software to analyze high-res hyper-spectral data
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
POSSIBLE APPLICATIONS E-heritage
Preservation of precise color
Medical imagingAnalysis of skins, neurons, blood, etc.
Material analysis / biological analysisSemiconductorsFossilsMicro-organismsBirds, insects
OUTCOMES Imaging system Software to analyze data
PROPOSED IMAGING SYSTEM
M. Ezra et al.
Giga-pixel Camera@ Microsoft research
Spectral transmittancevaries linearly
Large-format lens CCD
LINEAR VARIABLE FILTER
Filter
Monochrome camera
Rotational/translational stage
ADVANTAGES Giga-pixel spectral information
Microscopic level
Efficient combination Translational motion
Low costCost of the filter: ~ 1,000 $FWHF: ~ 4 nm to 8 nmTransmittance: ~ 30 to 40 %
TECHNICAL ISSUES Stitching
Filter causes intensity change
Low intensity vs. Acquisition timeDenoising
Data compression Wavelength ~ 80 dimension
Efficient data-acquisitionSize of the filter = bottleneck
CCDFilter
Useless
METHODS FOR VISUALIZATION & ANALYSIS Visualization
Development of GUI for user assistance
AnalysisMaterial estimation (spectral unmixing) Illumination/Surface reflectance separationSegmentation
SCHEDULEJuly Aug Sep Oct Nov Dec Jan Feb Mar Apr May June
A
B
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D
E
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H
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Survey on related cameras
Development of the camera
Writing a paper
Survey on spectral analysis
Developing a new spectral analysis method
Writing a paper
Presenting a paper about the sensor
Discussions with collaborators
Experiments with the sensor and the method
HOW TO CHECK PROGRESS Number of meetings
with collaborators
Number of days I spend at Microsoft research
Number of papers2
BUDGETTravel cost JPY Total
Travel to Beijing(Round trip: \50,000 x 2) 100,000
Travel expense for a conference(Travel cost: \300,000, Registration fee: \100,000) 400,000
Travel expense to measure cultural assets 100,000 600,000
Salaries JPY Total
Housing expense and salaries at Microsoft Research(\300,000 x 5 months) 1,500,000 1,500,000
Purchase of equipments JPY Total
Variable interference filter 100,000
Filter attachment 200,000
Artificial daylight for experiments 200,000
PC 100,000
Miscellaneous expense 300,000 900,000
MICROSOFT TOOLS & TECHNIQUES Giga-pixel camera
Visual studio
Office Live Meeting
Collaboration with Microsoft researchers
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
surfacesMIRU 2009 (oral presentation, in Japanese)