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Ugur Akpinar: End-to-end optimisation improves the performance of computational extended depth of field imaging

Tampereen yliopisto
PaikkakuntaKorkeakoulunkatu 1, Tampere
Hervannan kampus, Tietotalo, auditorio TB109 ja etäyhteys (linkki tulossa)
29.9.2023 12.00–16.00
Kielienglanti
PääsymaksuMaksuton tapahtuma
Ihmishahmo tohtorinhattu päässään, musta siluetti violetin kuultamalla taustalla.
In today’s evolving technological landscape, computational imaging is revolutionising imaging across a spectrum of applications by seamlessly integrating advanced hardware design with sophisticated software algorithms. In his doctoral dissertation, Ugur Akpinar delves into the transformative potential of end-to-end computational imaging shedding light on its profound relevance in the current era of visual technology.

One of the longstanding challenges in imaging systems is the quest for the extended depth of field imaging. This concept revolves around the range within which objects appear as sharp, an issue that has been the focus of extensive research for many years.

“My dissertation discusses a fresh perspective involving computational extended depth of field imaging through a technique known as wavefront coding. This method unites refractive lenses with novel diffractive phase masks to create system responses that maintain consistency across varying depths,” Ugur Akpinar explains.

Expanding the scope, the study delves into the domain of near-eye displays, with a particular focus on mitigating the “vergence-accommodation conflict”. This common issue in conventional near-eye displays often leads to significant visual discomfort and inaccuracies in depth perception.

“My research links this challenge to the limited depth of field in displays and explores avenues to design novel display systems that extend this depth of field while preserving image quality,” Akpinar says.

At the core of Akpinar’s research lies a meticulous process involving the co-design of optical elements and image processing algorithms. This intricate approach entails the development of physically precise differentiable models for computational cameras and near-eye displays that are integrated with state-of-the-art machine-learning techniques. The result is a joint optimisation of optical elements and parameters within neural processing modules, yielding a harmonious optimisation of extended depth-of-field imaging systems.

Public defence on Friday 29 September

The doctoral dissertation of MSc Ugur Akpinar titled Wavefront Coding Methods for Extended Depth of Field Image Acquisition and Display will be publicly examined at the Faculty of Information Technology and Communication Sciences of Tampere University at 12 o’clock on Friday 29 September 2023 in auditorium TB109 of Tietotalo building (Korkeakoulunkatu 1, Tampere). The Opponents will be Professor Ivo Ihrke from the University of Siegen, Germany, and Professor Henry Arguello from Industrial University of Santander, Colombia. The Custos will be Professor Atanas Gotchev from Tampere University.

The doctoral dissertation is available online.
The public defence can be followed via a remote connection. (Link to be added)