CIPHR - ERA Chair for Computational Imaging and Processing in High Resolution

Selle kollektsiooni püsiv URIhttps://hdl.handle.net/10062/91302

In the project, the Centre of Photonics and Computational Imaging is established at the UT. The combined application of photonics and computationally intensive data processing allows to enhance the image quality, resolution or add spatial dimension to the image beyond the physical or technical limits of the imaging system. By nature, the research is interdisciplinary and embraces the extensive competence of the University of Tartu in optics, spectroscopy, mathematics, computer science and their applications.

Sirvi

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Coded Aperture Imaging using Non-Linear Lucy-Richardson Algorithm
(2025) Xavier, Agnes Pristy Ignatius; Kahro, Tauno; Gopinath, Shivasubramanian; Tiwari, Vipin; Smith, Daniel; Kasikov, Aarne; Piirsoo, Helle-Mai; Ng, Soon Hock; Rajeswary, Aravind Simon John Francis; Vongsvivut, Jitraporn; Tamm, Aile; Kukli, Kaupo; Juodkazis, Saulius; Rosen, Joseph; Anand, Vijayakumar
Imaging involves the process of recording and reproducing images as close to reality as possible, encompassing both direct and indirect approaches. In direct imaging, the object is directly recorded. Coded aperture imaging (CAI) is an example of indirect imaging, that utilizes optical recording and computational reconstruction to obtain information about an object. Computational reconstruction can be achieved using different linear, non-linear, iterative, and deep learning algorithms. In this study, we proposed and demonstrated two computational reconstruction algorithms based on the non-linear Lucy-Richardson algorithm (NL-LRA), one for limited support images and another for full-view images based on entropy reduction. The efficacy of these algorithms has been validated through simulations and optical experiments carried out in visible and infrared (IR) light with different coded phase masks. The methods were also tested on a commercial IR microscope with internal Globar™ and synchrotron sources. The results obtained from the two algorithms were compared with those from their parent methods, and a notable improvement in both entropy and the convergence rate was observed. We believe the developed algorithms will drastically improve image reconstruction in incoherent imaging applications
Review of engineering techniques in chaotic coded aperture imagers
(2022) Anand, Vijayakumar; Rosen, Joseph; Juodkazis, Saulius
Coded aperture imaging (CAI) is a technique to image three-dimensional scenes with special controlled abilities. In this review, we survey several recently proposed techniques to control the parameters of CAI by engineering the aperture of the system. The prime architectures of these indirect methods of imaging are reviewed. For each design, we mention the relevant application of the CAI recorders and summarize this overview with a general perspective on this research topic.
Review of engineering techniques in chaotic coded aperture imagers
(Light: Advanced Manufacturing, 2022) Anand, V.; Rosen, J.; Juodkazis, S.
Coded aperture imaging (CAI) is a technique to image three-dimensional scenes with special controlled abilities. In this review, we survey several recently proposed techniques to control the parameters of CAI by engineering the aperture of the system. The prime architectures of these indirect methods of imaging are reviewed. For each design, we mention the relevant application of the CAI recorders and summarize this overview with a general perspective on this research topic.
Sculpting axial characteristics of incoherent imagers by hybridization methods
(2024) Gopinath, Shivasubramanian; Rajeswary, Aravind Simon John Francis; Anand, Vijayakumar
Axial resolving power (ARP) is one of the cornerstones of imaging systems. In conventional imaging systems, changing ARP by changing the numerical aperture affects also lateral resolving power (LRP). It is highly desirable to change ARP independent of LRP. Recently, incoherent digital holography (IDH) techniques were developed using sparse ensembles of Bessel, Airy and self-rotating beams that allow tuning ARP independent of LRP. In the above studies, the ARP was tuned by controlling the randomness which resulted in noisy reconstructions. In this study, we proposed and demonstrated two INCoherent Hybrid Imaging Systems (INCHIS) using a Bessel and spherical beam to change the ARP between the limits of Bessel and spherical beam independent of LRP. The first hybridization technique INCHIS-H1 requires pre-engineering of multifunctional phase masks using a recently developed modified Gerchberg-Saxton algorithm and an active device such as a spatial light modulator. The second hybridization technique INCHIS-H2 can be implemented using both active as well as passive optical elements with lens and axicon functions and the ARP is changed digitally after optical recording. While INCHIS-H1 requires pre-engineering of phase masks to change ARP like any conventional imaging system, the capability in INCHIS-H2 to change ARP post-recording opens a new pathway in imaging technology. Simulation results and proof-of-concept experimental results are presented. A recently developed Lucy-Richardson-Rosen algorithm has been used for image reconstruction for the above cases. We believe that the developed hybridization methods will revolutionize the field of IDH, computational imaging, computer vision and microscopy.

Sirvi

Sirvi CIPHR - ERA Chair for Computational Imaging and Processing in High Resolution Märksõna "Coded aperture imaging" järgi