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Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

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OpenSpyrit: an ecosystem for open single-pixel hyperspectral imaging.

Guilherme Beneti Martins, Laurent Mahieu-Williame, Thomas Baudier

|May 9, 2023

Summary

This summary is machine-generated.

OpenSpyrit provides an open-source ecosystem for reproducible hyperspectral single-pixel imaging research. It includes software and the first FAIR dataset, enabling robust benchmarking and advancing the field.

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Area of Science:

Optics and Photonics
Computational Imaging
Data Science

Background:

Reproducibility and benchmarking are critical challenges in hyperspectral single-pixel imaging.
Existing datasets and software tools often lack open access and standardization.

Purpose of the Study:

To introduce OpenSpyrit, an open-access and open-source ecosystem designed to foster reproducible research in hyperspectral single-pixel imaging.
To provide a standardized platform for data acquisition, reconstruction, and analysis in this field.

Main Methods:

Development of SPAS (Single-Pixel Acquisition Software) and SPYRIT (Single-Pixel Reconstruction Toolkit) in Python.
Creation of SPIHIM (Single-Pixel Hyperspectral Image Collection), the first open-access FAIR dataset for hyperspectral single-pixel imaging.
Reconstruction of hypercubes using inverse Hadamard transformation and a data-driven denoised completion network (DC-Net).

Main Results:

The SPIHIM collection contains 140 raw measurements and reconstructed hypercubes.
Standard reconstruction yields 64x64x2048 hypercubes with 2.3 nm spectral resolution.
DC-Net reconstruction achieves higher resolution (128x128x2048) and improved data quality.

Conclusions:

OpenSpyrit addresses the need for open data and software, promoting reproducibility and benchmarking in single-pixel imaging.
The ecosystem serves as a foundational reference for future advancements in hyperspectral single-pixel imaging technologies.