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ACM SIGGRAPH Asia 2017 (Transactions on Graphics)

 
High-Quality Hyperspectral Reconstruction Using a Spectral Prior
 
  Inchang Choi Daniel S. Jeon Giljoo Nam Diego Gutierrez* Min H. Kim  
             
    KAIST   *Universidad de Zaragoza, I3A  


  KAIST Dataset of Hyperspectral Reflectance Images
This is the supplemental material for the SIGGRAPH Asia 2017 Paper.
More information:
- Paper: http://vclab.kaist.ac.kr/siggraphasia2017p1/
- Codes: http://github.com/KAIST-VCLAB/deepcassi/

Capture setup
- Camera: Pointgrey Grasshopper 9.1MP Monochromatic (GS3-U3-91S6M-C)
- Lens: Jenoptik UV-VIS-IR 60mm f/4 apochromatic lens
- Filters: Liquid Crystal Tunable Filters (VariSpec VIS 400-720)
- Light Source: Xenon Illumination (Thorlab HPLS-30-4)

Notification
Spectral images below are reflectance images, which are normalized by the intensity of the reference white of Spectralon (calibrated 99% reflectance).

Please cite our paper if you use any of the free material in this website
  @Article{DeepCASSI:SIGA:2017,
  author  = {Inchang Choi and Daniel S. Jeon and Giljoo Nam 
             and Diego Gutierrez and Min H. Kim},
  title   = {High-Quality Hyperspectral Reconstruction 
             Using a Spectral Prior},
  journal = {ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2017)},
  year    = {2017},
  volume  = {36},
  number  = {6},
  pages   = {218:1-13},
  doi     = "10.1145/3130800.3130810",
  url     = "http://dx.doi.org/10.1145/3130800.3130810",
  }         
High-Quality Hyperspectral Images (click to download)

 





  How to read the files
An example MATLAB code for reading a hyperspectral EXR file:
(refer to our GitHub repository, 'openexr-matlab', for 'exrreadchannels')
codes:
example.m
exrreadchannels.m
exrreadchannels.mexmaci64
exrreadchannels.mexw64
 

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