Improving image quality of polarimetric cameras

Lead Research Organisation: University of Glasgow
Department Name: School of Physics and Astronomy


Thales are the leading company in Europe for high performance long wavelength infra-red (LWIR) imagers. Thales has been developing thermal imagers for more than 40 years, and is currently working on a unique polarimetric thermal imaging camera concept - the Polarimetric Catherine MP. Thermal imagers provide day and night imaging capability with good object discrimination (for example, telling the difference between animals and vehicles).

Further development work has been identified to progress the current camera capabilities. This work includes advanced signal, data and image processing development, some of which are already underway in house. The proposed project is integral part of this effort as it will address fundamental issues about the operation and performance of the detector, as well as investigating a novel approach to utilising the camera data (thermal and polarisation imagery) for deployment as part of a multi-modal imaging system. This will be achieved primarily through the application of existing expertise in Bayesian inference, imaging and polarisation in STFC-funded research groups (Astronmy and Institute of Gravitational Research) at the University of Glasgow. Algorithms will be developed with an aim to diagnosing and improving flat-fielding and polarimetric contrast. These algorithms will be tested using simulated data and test data acquired through experimentation and test field imaging.

This project will coordinate and support in-house R&D of Thales polarimetric imagers and help the company gain a better understanding at all levels of this technology and maximise its application in different markets


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Description We developed an algorithm that used multiple video frames to improve image resolution (super-resolution) using polarised long-wavelength infrared images. This algorithm removed edge artefacts present in the images and was also able to estimate the degree of polarisation for various regions of the image.
Exploitation Route The findings from this project have already been put to use in projects with industrial partners in medical instrumentation. Furthermore, the super-resolution algorithm is being assessed for us with hyperspectral imaging techniques that can have applications in security or medical imaging
Sectors Aerospace, Defence and Marine,Agriculture, Food and Drink,Chemicals,Construction,Digital/Communication/Information Technologies (including Software),Electronics,Energy,Environment,Healthcare,Leisure Activities, including Sports, Recreation and Tourism,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology,Security and Diplomacy,Transport,Other

Description The developed techniques from this project have been applied to address quality assurance issues in the production phase of medical imaging instrumentation at Optos PLC.
First Year Of Impact 2013
Sector Healthcare
Impact Types Economic

Description CENSIS
Amount £88,000 (GBP)
Organisation Government of Scotland 
Department Scottish Funding Council
Sector Public
Country United Kingdom
Start 11/2014 
End 10/2015
Description Scottish Sensor Systems Centre (S3C)
Amount £15,000 (GBP)
Organisation Government of Scotland 
Department Scottish Funding Council
Sector Public
Country United Kingdom
Start 08/2013 
End 12/2013
Title Bayesian inference for polarimetric imaging 
Description Technique for performing Bayesian inference on polarimetric camera images was developed 
Type Of Material Data analysis technique 
Provided To Others? No  
Impact Able to infer polarisation content of specific regions in images and determine uncertainties in these estimates 
Description Collaboration with Optos 
Organisation Optos plc
Department Optos
Country United Kingdom 
Sector Private 
PI Contribution Apply Bayesian expertise to develop artefact detection algorithm to aid quality assurance
Collaborator Contribution Expertise on Optos instrumentation and image data
Impact Have obtained funding from Scottish Funding Council for KT project with Optos as well as funding from an innovation centre
Start Year 2013