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<p class="MsoNormal"><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black">Fully-Funded PhD studentship in Computer Vision at the Colour & Imaging Lab, University of East Anglia, Norwich, UK <o:p></o:p></span></p>
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<p class="xmsonormal" style="margin-top:15.0pt;line-height:15.75pt"><b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black;background:white">Project Title:</span></b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black;background:white">
Designing cameras for Spectral Capture</span><span style="font-size:12.0pt;font-family:"Arial",sans-serif;background:white"><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-bottom:7.5pt;background:white"><b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black">Project Description: </span></b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333">If we
could take pictures of the world where instead of recording colour (i.e. the RGB ) at each pixel we measured the per-pixel radiance spectrum then we could solve many problems that are not currently solvable in colour imaging (ranging from better image reproduction [1], to
better medical diagnoses [2] and remote sensing [3]). The overarching aim of this project is to design an N-sensor (N>3) camera that can – with the addition of powerful inference algorithms - be used to measure spectral data. <o:p></o:p></span></p>
<p class="MsoNormal" style="margin-bottom:7.5pt;background:white"><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333">It turns out that given an RGB or N-sensor camera response there are many possible spectra that might have induced
it. In the first part of this project we will develop algorithms for estimating the set of all possible spectra from a camera response [4]. Clearly, if for a given camera its responses map to spectra with small uncertainty (the set of possible spectra is on
average small) then this camera is a good candidate for spectral measurement . In this project we wish to find cameras that recover spectra with small uncertainty. This work will be carried out in close collaboration with Spectricity, our project partners. <o:p></o:p></span></p>
<p class="MsoNormal" style="margin-bottom:7.5pt;background:white"><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333">The proposed research will take place in the Colour & Imaging Lab (C&IL) at the University of East Anglia (Norwich,
UK) and is in collaboration with Spectricity. The C&IL is a centre of excellence for colour imaging. The successful candidate will join a team of 10 PhD students and 2 Post-doctoral research fellows.<o:p></o:p></span></p>
<p class="MsoNormal" style="margin-bottom:7.5pt;background:white"><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333">For more information on the supervisor for this project, please go here: <a href="https://www.findaphd.com/common/clickCount.aspx?theid=131098&type=184&DID=434&url=https%3a%2f%2fwww.uea.ac.uk%2fstories%2fprof-graham-finlayson" target="_blank"><span style="color:#D91B5C">https://www.uea.ac.uk/stories/prof-graham-finlayson</span></a><o:p></o:p></span></p>
<p class="MsoNormal" style="margin-bottom:7.5pt;background:white"><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333">Entry requirements: Acceptable first degree 1st or Masters in Computer Science, Physics, Maths or other numerate discipline.<o:p></o:p></span></p>
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<b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333">References:<o:p></o:p></span></b></p>
<p class="MsoNormal" style="background:white"><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333">i) Lin Y.; Finlayson G.D. Physically plausible spectral reconstruction. Sensors. 2020, doi.org/10.3390/s20216399<br>
ii) Zhang, Y.; Mou, X.; Wang, G.; Yu, H. Tensor-based dictionary learning for spectral CT reconstruction. IEEE Trans. Med Imaging 2016, 36, 142–154.<br>
iii) Chen, C.; Li, W.; Su, H.; Liu, K. Spectral-spatial classification of hyperspectral image based on kernel extreme learning machine. Remote. Sens. 2014, 6, 5795–5814<br>
iv) Morovic, P.; Finlayson, G.D. Metamer-set-based approach to estimating surface reflectance from camera RGB. J. Opt. Soc. Am. A 2006, 23, 1814–1822.<o:p></o:p></span></p>
<p class="MsoNormal" style="background:white"><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333"><o:p> </o:p></span></p>
<p style="background:white"><b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black">Deadline: 30<sup>th</sup> Apr, 2021</span></b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black">,<b>
</b>Projects will start on the 1<sup>st</sup> Oct 2021</span><span style="font-size:12.0pt;font-family:"Arial",sans-serif"><o:p></o:p></span></p>
<p style="background:white"><b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black">Details and how to apply:</span></b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black"> <a href="https://www.findaphd.com/phds/project/designing-cameras-for-spectral-capture-finlaysong-u21spec/?p131098">https://www.findaphd.com/phds/project/designing-cameras-for-spectral-capture-finlaysong-u21spec/?p131098</a></span><span style="font-size:12.0pt;font-family:"Arial",sans-serif"><o:p></o:p></span></p>
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<p class="MsoNormal" style="margin-bottom:7.5pt;background:white"><b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:black">Funding Notes: </span></b><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#333333">This PhD studentship
is funded for 3 years by Spectricity. Funding is available to UK, EU & international applicants and includes tuition fees, an annual stipend of £15,744 in year 1, rising to £16,702 in year 3. The studentship length is 3 years.<o:p></o:p></span></p>
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