Opti-MSFA: a toolbox for generalized design and optimization of multispectral filter arrays.
View / Open Files
Authors
Sawyer, Travis W
Taylor-Williams, Michaela
Tao, Ran
Xia, Ruqiao
Bohndiek, Sarah E
Publication Date
2022-02-28Journal Title
Opt Express
ISSN
1094-4087
Publisher
Optica Publishing Group
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Sawyer, T. W., Taylor-Williams, M., Tao, R., Xia, R., Williams, C., & Bohndiek, S. E. (2022). Opti-MSFA: a toolbox for generalized design and optimization of multispectral filter arrays.. Opt Express https://doi.org/10.1364/OE.446767
Abstract
Multispectral imaging captures spatial information across a set of discrete spectral channels and is widely utilized across diverse applications such as remote sensing, industrial inspection, and biomedical imaging. Multispectral filter arrays (MSFAs) are filter mosaics integrated atop image sensors that facilitate cost-effective, compact, snapshot multispectral imaging. MSFAs are pre-configured based on application-where filter channels are selected corresponding to targeted absorption spectra-making the design of optimal MSFAs vital for a given application. Despite the availability of many design and optimization approaches for spectral channel selection and spatial arrangement, major limitations remain. There are few robust approaches for joint spectral-spatial optimization, techniques are typically only applicable to limited datasets and most critically, are not available for general use and improvement by the wider community. Here, we reconcile current MSFA design techniques and present Opti-MSFA: a Python-based open-access toolbox for the centralized design and optimization of MSFAs. Opti-MSFA incorporates established spectral-spatial optimization algorithms, such as gradient descent and simulated annealing, multispectral-RGB image reconstruction, and is applicable to user-defined input of spatial-spectral datasets or imagery. We demonstrate the utility of the toolbox by comparing against other published MSFAs using the standard hyperspectral datasets Samson and Jasper Ridge, and further show application on experimentally acquired fluorescence imaging data. In conjunction with end-user input and collaboration, we foresee the continued development of Opti-MSFA for the benefit of the wider research community.
Sponsorship
Cancer Research UK (C14303/A17197)
Engineering and Physical Sciences Research Council (EP/R003599/1)
Identifiers
External DOI: https://doi.org/10.1364/OE.446767
This record's URL: https://www.repository.cam.ac.uk/handle/1810/332928
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.