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Single-Pixel Hyperspectral Imaging (SPIHIM) Datasets

Version 1.0 and later

Our datasets are made publicly available following FAIR (findability, accessibility, interoperability, reusability) principles through the pilot warehouse

Reference:

  • G. Beneti-Martin, L Mahieu-Williame, T Baudier, N Ducros, "OpenSpyrit: an Ecosystem for Reproducible Single-Pixel Hyperspectral Imaging," Optics Express, Vol. 31, No. 10, (2023). DOI. Main PDF. Supplemental document.

Version 0

License: The SPIHIM datasets are distributed under the Creative Commons Attribution 4.0 International license (CC-BY 4.0)

Reference: Please reference this work

  • A Lorente Mur, B Montcel, F Peyrin, N Ducros. Deep neural networks for single-pixel compressive video reconstruction. SPIE Photonics Europe, Proc. vol. 11351, Unconventional Optical Imaging II, pp.27, Apr 2020, France. ⟨hal-02547800⟩

Contact: nicolas.ducros@insa-lyon.fr, CREATIS Laboratory, University of Lyon, France.

Setup Description

Hardware

The set-up is depicted below and in detail [ALM2020]. The telecentric lens (TL; Edmund Optics 62901) is positioned such that its image side projects the image of the sample (S) onto the digital micro-mirror device (DMD; vialux V-7001), which is positioned at the object side of the lens. The object is transparent and is illuminated by a LED lamp (L; Thorlabs LIUCWHA/M00441662). The DMD can implement different light patterns by reflection of the incident light onto a relay lens (RL), which projects the light into an optical fiber (OF; Thorlabs FT1500UMT 0.39NA). This optical fiber is connected to a compact spectrometer (SM; BWTek examplar BRC115P-V-ST1). A filter wheel (FW) containing neutral optical densities is placed behind the lamp to reduce the light flux

Mathematical Model

The setup acquires M = α HF where F in R n x λ represents the sample hypercube, H in R m x n the measurement matrix, and α is a multiplicative factor that depends on and the optical density. The measurement matrix contains the patterns that are uploaded onto the DMD. Here, m represents the number of patterns, n the number of pixels of the patterns, and λ the number of spectral bins.

The multiplicative factor is given by α = φ 10-OD Δt (in photons), where φ (in photons/s) represents the given light flux, OD is neutral optical density and Δt is the integration time.

Hadamard Acquisitions

We acquire Hadamard patterns that we split into positive and negative parts, which are concatenated in the measurement matrix. Precisely, Hm contains the positive parts and Hm+1 the negative parts, such that Hm - Hm+1 is a Hadamard pattern.

We sequentially upload onto the DMD all of the m = 2 x 4096 Hadamard (split) patterns of dimension n = 64 x 64 pixels. The patterns in PNG format can be downloaded here.

We acquire different datasets for the same object by selecting different neutral densities OD and different integration times Δt.

Summary of the SPIHIM datasets

The following datasets are provided

We provide the description of each measurement session in the sections below.

Data Reading, measurement matrix, and reconstruction

Based on SPIRiT, we provide matlab scripts that

  • read, reconstruct and plot the datasets (see ./scripts/read_*_.m)
  • build the forward operator H that maps the image of the sample the onto the measured Hadamard coefficients (see ./scripts/build_forward_operator.m)

The (full) Hadamard matrix H in R n x n can be downloaded here. It applies to a measurement vector in R n, where the missing coefficients have been field with zeros. To compute the (reduced) measurement matrix H in R m x n, see ./scripts/build_forward_operator.m.

The acquisition is such that the patterns with maximum variance are acquired first. We provide here the covariance matrix used to defined the acquisition order ; it was computed on the STL-10 image dataset.

Description of the SPIHIM datasets

04-Feb-2020 session

We acquired four samples:

  • A star sector target printed on a paper sheet in black an white
  • A star sector target printed on a paper sheet printed in color according to a Hue color wheel
  • A paper sheet with no printing
  • No object, i.e., the illumination LED lamp directly
Filename M Δt (ms) Comment
SiemensBW1a_raw.mat 408 4 black and white star sector
SiemensColor8a_raw.mat 408 32 color star sector
SiemensColor8b_raw.mat 1228 32 color star sector
mydata_raw.mat 512 4
paperSheet1b_raw.mat 1228 4 paper sheet
paperSheet2b_raw.mat 1228 8 paper sheet
paperSheet4b_raw.mat 1228 16 paper sheet
siemensStar1a_raw.mat 408 4 black and white star sector
siemensStar1b_raw.mat 1228 4 black and white star sector
siemensStar2a_raw.mat 408 8 black and white star sector
siemensStar2b_raw.mat 1228 8 black and white star sector
siemensStar4a_raw.mat 408 16 black and white star sector
siemensStar4b_raw.mat 1228 16 black and white star sector
siemensStar8a_raw.mat 408 32 black and white star sector
siemensStar8b_raw.mat 1228 32 black and white star sector
siemensStarColor1b_raw.mat 1228 4 color star sector
siemensStarColor2b_raw.mat 1228 8 color star sector
siemensStarColor4b_raw.mat 1228 16 color star sector
siemensStarColor4c_raw.mat 2456 16 color star sector
siemensStarColor8d_raw.mat 4096 32 color star sector
whiteLED1a_raw.mat 408 4 no object

11-Jun-2020 session

First, we acquired the LED source directly with no sample

Filename Δt (ms) OD (-) Comment
noObjectD_1_0.0_raw.mat 4 0.0 Saturate
noObjectD_1_0.3_01_raw.mat 4 0.3 Repeat same measurement 4x to simulate longer Δt while avoiding saturation
noObjectD_1_0.3_02_raw.mat 4 0.3
noObjectD_1_0.3_03_raw.mat 4 0.3
noObjectD_1_0.3_04_raw.mat 4 0.3
noObjectD_1_0.3_raw.mat 4 0.3
noObjectD_1_0.6_raw.mat 4 0.6
noObjectD_1_1.0_raw.mat 4 1.0
noObjectD_1_1.3_raw.mat 4 1.3

Second, we acquired the star sector target

Filename Δt (ms) OD (-) Comment
starSectorD_2_0.0_01_raw.mat 8 0.0 Repeat same measurement 4x to simulate longer Δt while avoiding saturation
starSectorD_2_0.0_02_raw.mat 8 0.0
starSectorD_2_0.0_03_raw.mat 8 0.0
starSectorD_2_0.0_04_raw.mat 8 0.0
starSectorD_2_0.0_05_raw.mat 8 0.0
starSectorD_2_0.0_06_raw.mat 8 0.0
starSectorD_2_0.0_07_raw.mat 8 0.0
starSectorD_2_0.0_08_raw.mat 8 0.0
starSectorD_2_0.0_09_raw.mat 8 0.0
starSectorD_2_0.0_10_raw.mat 8 0.0
starSectorD_2_0.0_raw.mat 8 0.0
starSectorD_2_0.3_raw.mat 8 0.3
starSectorD_2_0.6_raw.mat 8 0.6
starSectorD_2_1.0_raw.mat 8 1.0
starSectorD_2_1.3_raw.mat 8 1.3

Third, we acquire the star sector target that was off-centered

Filename Δt (ms) OD (-) Comment
R1L1S2P_1_0.0_raw.mat 4 0.0 Shows the 'R1L1S2P' writing
R1L1S2P_1_0.3_raw.mat 4 0.3
R1L1S2P_1_0.6_raw.mat 4 0.6
R1L1S2P_1_1.0_raw.mat 4 1.0
R1L1S2P_1_1.3_raw.mat 4 1.3
Thorlabs_1_0.0_raw.mat 4 0.0 Shows the 'THORLABS' writing
Thorlabs_1_0.3_raw.mat 4 0.3
Thorlabs_1_0.6_raw.mat 4 0.6

Finally, we acquire images from the STL10 databaset

Filename Δt (ms) OD (-) Comment
stl10_01_32ms_cp_raw.mat 32 0.0 horse displayed on my cell phone (cp)
stl10_01_32ms_ps_raw.mat 32 0.0 horse printed on a paper sheet (ps)
stl10_01_64ms_ps_raw.mat 64 0.0 horse printed on a paper sheet (ps)
stl10_08_32ms_ps_raw.mat 32 0.0 bird printed on a paper sheet (ps)

01-Jul-2020 session

First, we acquired the LED source directly with no sample. Note that the noObjectF1 series and the noObjectF2 series refer to two different positions of the LED lamp.

Filename Δt (ms) OD (-) Comment
noObjectF1_1_0.3_01_raw.mat 4 0.3 Repeat same measurement 15x to simulate longer Δt while avoiding saturation
noObjectF1_1_0.3_02_raw.mat 4 0.3
noObjectF1_1_0.3_03_raw.mat 4 0.3
noObjectF1_1_0.3_04_raw.mat 4 0.3
noObjectF1_1_0.3_05_raw.mat 4 0.3
noObjectF1_1_0.3_06_raw.mat 4 0.3
noObjectF1_1_0.3_07_raw.mat 4 0.3
noObjectF1_1_0.3_08_raw.mat 4 0.3
noObjectF1_1_0.3_09_raw.mat 4 0.3
noObjectF1_1_0.3_10_raw.mat 4 0.3
noObjectF1_1_0.3_11_raw.mat 4 0.3
noObjectF1_1_0.3_12_raw.mat 4 0.3
noObjectF1_1_0.3_13_raw.mat 4 0.3
noObjectF1_1_0.3_14_raw.mat 4 0.3
noObjectF1_1_0.3_15_raw.mat 4 0.3
noObjectF1_1_0.3_raw.mat 4 0.3
noObjectF1_1_0.6_raw.mat 4 0.6
noObjectF2_1_0.3_01_raw.mat 4 0.3 Not the same LED lamp position as in the noObjectF1 series. We repeat same measurement 9x to simulate longer Δt while avoiding saturation
noObjectF2_1_0.3_02_raw.mat 4 0.3
noObjectF2_1_0.3_03_raw.mat 4 0.3
noObjectF2_1_0.3_04_raw.mat 4 0.3
noObjectF2_1_0.3_05_raw.mat 4 0.3
noObjectF2_1_0.3_06_raw.mat 4 0.3
noObjectF2_1_0.3_07_raw.mat 4 0.3
noObjectF2_1_0.3_08_raw.mat 4 0.3
noObjectF2_1_0.3_09_raw.mat 4 0.3
noObjectF2_1_0.3_raw.mat 4 0.3 Not the same LED lamp position as in the noObjectF1 series
noObjectF2_1_0.6_raw.mat 4 0.6
noObjectF2_1_1.0_raw.mat 4 1.0
noObjectF2_1_1.3_raw.mat 4 1.3
Filename Δt (ms) OD (-) Comment
stl10_03_1_0.0_raw.mat
stl10_05_1.5_0.0_01_raw.mat
stl10_05_1.5_0.0_02_raw.mat
stl10_05_1.5_0.0_03_raw.mat
stl10_05_1.5_0.0_04_raw.mat
stl10_05_1.5_0.0_05_raw.mat
stl10_05_1.5_0.0_06_raw.mat
stl10_05_1_0.0_raw.mat
stl10_05_1_0.3_raw.mat
stl10_05_1_0.6_raw.mat

18-Nov-2020 session

Contrary to previous datasets, the DMD frequency is set to 1 kHz and the DMD patterns are 4-bit (see par.DMD_fr and par.bitplane).

Filename M Δt (ms) Comment
noObject_01ms_raw.mat 8192 1
noObject_10ms_raw.mat 8192 10
starSector_01ms_raw.mat 8192 1 Starsector in the image plane
starSector_variableFilter_C_10ms_raw.mat 8192 10 Starsector in the image plane, filter between lamp and image plane
variableFilter_01ms_raw.mat 8192 1 Filter in the image plane
variableFilter_10ms_raw.mat 8192 10 Filter in the image plane
variableFilter_B_01ms_raw.mat 8192 1 Filter in the image plane
variableFilter_B_10ms_raw.mat 8192 10 Filter in the image plane
variableFilter_C_10ms_raw.mat 8192 10 Filter in the image plane `

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