A Spatio-chromatic colour appearance model for retargeting high dynamic range image appearance across viewing conditions

Lead Research Organisation: University of East Anglia
Department Name: Computing Sciences

Abstract

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Publications

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Finlayson G (2022) TM-Net: A Neural Net Architecture for Tone Mapping. in Journal of imaging

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Hemrit G (2020) Providing a Single Ground-Truth for Illuminant Estimation for the ColorChecker Dataset. in IEEE transactions on pattern analysis and machine intelligence

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McVey J (2021) Towards a Generic Neural Network Architecture for Approximating Tone Mapping Algorithms in London Imaging Meeting

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McVey J (2019) Least-Squares Optimal Contrast Limited Histogram Equalisation in Color and Imaging Conference

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McVey J (2020) Linear Histogram Adjustment for Image Enhancement in London Imaging Meeting

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McVey J. (2019) Least-squares optimal contrast limited histogram equalisation in Final Program and Proceedings - IS and T/SID Color Imaging Conference

 
Description Our data demonstrate a previously unknown characteristic of the visual system at high luminance. Using the data, we developed a new, fundamental model of the human visual system (the spatio-chromatic sensitivity function) that can predict the visibility of black-and-white and colour patterns under very dim (0.02 cd/m^2) and very bright (7000 cd/m^2) viewing conditions. We are currently investigating the application of the model in several problems, including high-dynamic-range video compression and modelling of colour appearance. Future advances of tone mapping are concurrently being investigated.
Exploitation Route Our work has implications for improving future HDR image and video coding standards. Our work can also help to design better colour spaces and metrics for high-dynamic-range content.
Sectors Creative Economy,Electronics
URL https://www.cl.cam.ac.uk/research/rainbow/projects/hdr-csf/
 
Description EU Real Vision ITN 
Organisation Technical University of Denmark
Country Denmark 
Sector Academic/University 
PI Contribution RealVision: The aim of realistic digital imaging is the creation of high quality imagery, which faithfully represents the physical environment. The ultimate goal is to create images, which are perceptually indistinguishable from a real scene. The RealVision network brings together leading universities and centres focused on industrial development and companies in multimedia, optics, visual communication, visual computing, computer graphics, and human vision research across Europe, with the aim of training a new generation of scientists, technologists, and entrepreneurs that will move Europe into a leading role in innovative hyper-realistic imaging technologies. I collaborate in part through Spectral Edge Ltd
Collaborator Contribution RealVision: The aim of realistic digital imaging is the creation of high quality imagery, which faithfully represents the physical environment. The ultimate goal is to create images, which are perceptually indistinguishable from a real scene. The RealVision network brings together leading universities and centres focused on industrial development and companies in multimedia, optics, visual communication, visual computing, computer graphics, and human vision research across Europe, with the aim of training a new generation of scientists, technologists, and entrepreneurs that will move Europe into a leading role in innovative hyper-realistic imaging technologies.
Impact This is an EU ITN. The outcome will be trained PhDs and their impact (through internships) with the academic institutes and companies involved.
Start Year 2019