File size: 1,598 Bytes
a39aaf9 9976b06 25a9044 9976b06 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | ---
license: unknown
---
# Description
The `exr` folder contains a high-resolution dataset, consisting of 30 hyperspectral images covering a wide spectral range.
The acquisitions have 31 channels in the range 420-720 nm, with a separation of 10 nm.
The spectral images are reflectance images, which are normalized by the intensity of the reference white of Spectralon (calibrated 99% reflectance).
# 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)
# How to read the files
An example MATLAB code for reading a hyperspectral EXR file is given in
`example.m` under `code`.
For `exrreadchannels`, you can refer to the GitHub repository:
<https://github.com/KAIST-VCLAB/openexr-matlab>
# Credits
The dataset was originally collected from:
<http://vclab.kaist.ac.kr/siggraphasia2017p1/kaistdataset.html>
If you use this dataset, please cite:
```bibtex
@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",
}
```
|