Single-Pixel Image Reconstruction Toolbox (SPIRiT) Version 2.1, 1st April 2020.
This package contains Matlab scripts and functions that simulate the acquisition and reconstruction of an image with a single-pixel camera.
- Recontruction by completion of missing data
help datcomp
- Fast Hadamard 2D transform
help fwht2
- Pre-processing and playing with the STL-10 database
help preprocess_stl10
help loadprep_stl10
SPIRiT 2.1 implements:
- (from v2.1) The Bayesian completion method described in [3].
See
main_completion_stl10.m
. - (from v2.0) The SNMF pattern generalization method described in [2].
See
main_abswp_simulation.m
andmain_abswp_experimental.m
. - (from v2.0) The ABS-WP adaptive acquisition method described in [1].
See
main_abswp_simulation.m
andmain_abswp_experimental.m
.
The .\function\
folder contains the functions that are called in the above scripts.
The .\data\
folder contains:
- three PNG images that are processed in
main_abswp_simulation.m
- two experimental datasets (MAT-files) that can be processed by
main_abswp_experimental.m
. For details, see.\data\Readme.txt
.
The .\reference\
folder contains the PDF of [1], [2], and [3].
We provide:
- A function to preprocess the STL-10 database that can be downloaded at https://ai.stanford.edu/~acoates/stl10/
- Two experimental datasets (Department of Physics, Politecnico di Milano, Italy) of the Jaszczak target acquired using wavelet patterns, initially published in [1]. For details, see
.\data\Readme.txt
.
Just make sure to add .\function\
to your Matlab search path.
path(fullfile(pwd,'function'),path);
SPIRiT may require one of the following toolboxes to run:
- Image Processing Toolbox (MathWorks)
- Statistics and Machine Learning Toolbox (MathWorks), to corrupt data with Poisson noise
- Wavelab850.
Note: If required, make sure Wavelab850 appears at the top of your search path to avoid conflits
nicolas.ducros@insa-lyon.fr, University of Lyon, France.
SPIRiT is distributed freely under Creative Commons Attribution-ShareAlike 4.0 International license (CC-BY-SA 4.0)
[3] N. Ducros et al., "A completion network for reconstruction from compressed acquisition', IEEE ISBI, 2020. https://hal.archives-ouvertes.fr/hal-02342766/document
[2] F. Rousset et al., "A semi nonnegative matrix factorization technique for pattern generalization in single-pixel imaging", IEEE Transactions on Computational Imaging, 4(2), 284-294, 2018. https://doi.org/10.1109/TCI.2018.2811910 https://hal.archives-ouvertes.fr/hal-01635461/document
[1] F. Rousset et al., "Adaptive basis scan by wavelet prediction for single-pixel imaging", IEEE Transactions on Computational Imaging, 3(1), 36-46, 2017. http://dx.doi.org/10.1109/TCI.2016.2637079 https://hal.archives-ouvertes.fr/hal-01314314/document