PhD Studentship in Theory and Practice of High Dynamic Range Imaging (Fixed Term)

Fixed-term: The funds for this post are available for 3.5 years. Dive into the future of visual technology with a studentship at the forefront of modern imaging science, where high dynamic range (HDR) imaging is redefining the way smartphone cameras and displays capture the world. Despite HDR becoming the new standard, many classic image-processing algorithms and generative models remain limited to the world of standard dynamic range (SDR). This project seeks to bridge that divide, unifying methods and technologies designed for both SDR and HDR content-spanning still images and video alike. You'll explore the exciting frontiers of HDR multispectral imaging and imaging with non-standard primaries, pushing the boundaries of colour accuracy and personalising colour reproduction for all, including those with colour vision deficiencies. The work doesn't stop there: you'll also investigate advanced tone-mapping and inverse-tone-mapping techniques to translate seamlessly between HDR and SDR worlds, ensuring consistent colour and contrast perception across luminance levels. Building on cutting-edge psychophysical models, this research promises to reshape how we see, capture, and reproduce the visual world. In brief, the topics of interest include: • Principled methods for adapting SDR algorithms to HDR content [1,2] • Multispectral HDR imaging, with the focus on colour accuracy and colour reproduction that accounts for the differences in colour perception [3,4] • Mapping between SDR and HDR that preserves colour and contrast appearance, and relies on psychophysical models of human vision [5-9] • You will work with both machine learning and psychophysical models of human vision [5,9,10]. • The study may also involve psychophysical experimentation to collect novel data on human colour vision and image quality [10] This project is a collaboration between Prof. Rafal Mantiuk (University of Cambridge) and Prof. Graham Finlayson (The Colour & Imaging Lab, The University of East Anglia). Profs Mantiuk and Finlayson have a long track record of working in HDR Imaging, Displays, and Psychophysical evaluation, [1,2,3,4,5,6]. This project is funded by a donation through Apple Inc. (Cambridge). It is expected that the successful student will intern with Apple during one Summer of the PhD. The project is based at the University of Cambridge. Applicants must contact Prof. Rafal Mantiuk (rafal.mantiuk@cl.cam.ac.uk) in advance to assess topic and background fit. Please include a CV and a 2-paragraph research statement that shows evidence of engagement with this advert. Further information on the PhD in Computer Science programme can be found at: https://www.postgraduate.study.cam.ac.uk/courses/directory/cscspdpcs/apply All applications should be made online via the University's Applicant Portal: https://www.postgraduate.study.cam.ac.uk/courses/directory/cscspdpcs/apply. Please quote the reference NR50548 in the Research Topic so that applications can be routed directly to Prof. Mantiuk. Applications should include academic transcripts, a CV, a research proposal, and 2 references. An application is only complete when all supporting documents, including the 2 academic references, are submitted. It is your responsibility to ensure that both referees submit their references before the closing date. The research proposal should expand on at least two topics listed in the bullet points above. This studentship provides full approved tuition fees and maintenance at recommended UKRI rates. Both home and overseas students are welcome to apply. It is expected that the selected candidate will start in January 2027. We encourage groups currently underrepresented in Engineering and Physical Science subjects. Amongst UK-domiciled students, this includes women, Black British, British Bangladeshi and British Pakistani applicants. Amongst UK-domiciled and international applicants, we also particularly welcome applications from people from low-income backgrounds, mature students, care-experienced students, and students from families where no parent or care-giver went to university. Further information can be found on our widening participation webpages https://www.postgraduate.study.cam.ac.uk/apply/before/widening-access [1] A. Y. Ke et al., 'Training Neural Networks on RAW and HDR Images for Restoration Tasks', New Trends in Image Restoration and Enhancement (CVPR workshop), 2025. [2] R. K. Mantiuk and M. Azimi, 'PU21: A novel perceptually uniform encoding for adapting existing quality metrics for HDR', in 2021 Picture Coding Symposium (PCS), IEEE, June 2021, pp. 1-5. doi: 10.1109/PCS50896.2021.9477471. [3] G. D. Finlayson and Y. Zhu, 'Designing Color Filters That Make Cameras More Colorimetric', IEEE Trans. on Image Process., vol. 30, pp. 853-867, 2021, doi: 10.1109/TIP.2020.3038523. [4] H. Gao, R. K. Mantiuk, and G. D. Finlayson, 'Color-Accurate Camera Capture with Multispectral Illumination and Multiple Exposures', Computer Graphics Forum, vol. 43, no. 7, p. e15252, Oct. 2024, doi: 10.1111/cgf.15252. [5] R. Mantiuk, S. Daly, and L. Kerofsky, 'Display adaptive tone mapping', ACM Transactions on Graphics (Proc. of SIGGRAPH), vol. 27, no. 3, p. 68, 2008, doi: 10.1145/1360612.1360667. [6] J. Vazquez-Corral, G.D. Finlayson and L. Herranz, "Improving the perception of low-light enhanced images", Optics Express, 5174-5190, 2024. [7] G.D. Finlayson and J. McVey, "TM-Net: A Neural Net Architecture for Tone Mapping", Journal of Imaging, 325, 2022. [8] S. Westland, G.D. Finlayson, P. Lai, Q. Pan, J. Yang and Y. Chen. "A computational method for predicting color palette discriminability", Color Research & Application, 2024 [9] G. Eilertsen, J. Kronander, G. Denes, R. K. Mantiuk, and J. Unger, 'HDR image reconstruction from a single exposure using deep CNNs', ACM Transaction on Graphics, vol. 36, no. 6, p. Article 178, 2017. [10] Supra-threshold Contrast Perception in Augmented Reality Dongyeon Kim, Maliha Ashraf, Alexandre Chapiro, Rafal K. Mantiuk. In: Proc. of SIGGRAPH Asia 2025, 2025 Please quote reference NR50548 on your application and in any correspondence about this vacancy. The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.