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  Prof G D Finlayson  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Most prior art image fusion algorithms are based on two assumptions. First, N-channel input images (e.g. the N=4 channel R, G, B and near-infrared) are fused into a single channel equivalent fused image [1]. And, second, that – other than the fused data capturing all the detail of the channels – there is not a simple structural relationship between the fused image and any of the N-channel input images.

In this PhD project, the successful candidate will develop a guided colour image fusion algorithm that maps N-channel images to M-channels (where M<N and is typically 3 i.e. a colour image). Further, the fused image will be guided by the structure in the original colour image. For the RGB+NIR example, the fused image will ‘look like’ the original image but with some extra detail composited from the NIR channel. The prior art “spectral edge” image fusion algorithm [2] can be viewed as a guided colour image fusion algorithm but, there, the concept of guide is at a very low level. The project will develop image fusion algorithms based on higher level semantic concepts including image relighting [3] and semantic decompositions [4]. The image fusion research will take place in the context of the wider ‘Future Colour Imaging’ project [5].

The successful candidate will join the Colour & Imaging Lab (the C&IL) in the School of Computing Sciences at UEA. The C&IL is one of our largest labs and currently comprises 10 PhD students and 3 postdoctoral fellows. 


Funding Notes

This PhD project is UEA funded studentship covering stipend (£15,609 pa in 2021-22), tuition fees (Home only) and research costs. International applicants (EU/non-EU) are eligible for UEA funded studentships but they are required to fund the difference between Home and International tuition fees (which for 2021-22 are detailed on the University’s fees pages at https://www.uea.ac.uk/about/university-information/finance-and-procurement/finance-information-for-students/tuition-fees)

References

i) D. Socolinsky and L. Wolff, “Multispectral image visualization through first-order fusion”, IEEE Transactions on Image Processing, 2002.
ii) D. Connah, M.S. Drew and G.D. Finlayson, “Spectral edge: gradient-preserving spectral mapping for image fusion”, The Journal of the Optical Society of America A, 2015
iii) J. Vazquez and G.D. Finlayson, “Coupled Retinex,” The 27th Color and Imaging Conference, 2019
iv) N. Carion et al., “End-to-end Object Detections using Transforms,” The European Conference on Computer Vision, 2020.
v) gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/S028730/1
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