Browsing by Author "Valdma, Sandhra-Mirella"

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Deep Deconvolution of Object Information Modulated by a Refractive Lens Using Lucy-Richardson-Rosen Algorithm
(2022) Praveen, P.A.; Arockiaraj, Francis Gracy; Gopinath, Shivasubramanian; Smith, Daniel; Kahro, Tauno; Valdma, Sandhra-Mirella; Bleahu, Andrei; Ng, Soon Hock; Reddy, Andra Naresh Kumar; Katkus, Tomas; Rajeswary, Aravind Simon John Francis; Ganeev, Rashid A.; Pikker, Siim; Kukli, Kaupo; Tamm, Aile; Juodkazis, Saulius; Anand, Vijayakumar
A refractive lens is one of the simplest, most cost-effective and easily available imaging elements. Given a spatially incoherent illumination, a refractive lens can faithfully map every object point to an image point in the sensor plane, when the object and image distances satisfy the imaging conditions. However, static imaging is limited to the depth of focus, beyond which the point-to-point mapping can only be obtained by changing either the location of the lens, object or the imaging sensor. In this study, the depth of focus of a refractive lens in static mode has been expanded using a recently developed computational reconstruction method, Lucy-Richardson-Rosen algorithm (LRRA). The imaging process consists of three steps. In the first step, point spread functions (PSFs) were recorded along different depths and stored in the computer as PSF library. In the next step, the object intensity distribution was recorded. The LRRA was then applied to deconvolve the object information from the recorded intensity distributions during the final step. The results of LRRA were compared with two well-known reconstruction methods, namely the Lucy-Richardson algorithm and non-linear reconstruction.
Nonlinear Reconstruction of Images from Patterns Generated by Deterministic or Random Optical Masks—Concepts and Review of Research
(Journal of Imaging, 2022) Smith, Daniel; Gopinath, Shivasubramanian; Arockiaraj, Francis Gracy; Reddy, Andra Naresh Kumar; Balasubramani, Vinoth; Kumar, Ravi; Dubey, Nitin; Ng, Soon Hock; Katkus, Tomas; Selva, Shakina Jothi; Renganathan, Dhanalakshmi; Kamalam, Manueldoss Beaula Ruby; Rajeswary, Aravind Simon John Francis; Navaneethakrishnan, Srinivasan; Inbanathan, Stephen Rajkumar; Valdma, Sandhra-Mirella; Praveen, Periyasamy Angamuthu; Amudhavel, Jayavel; Kumar, Manoj; Ganeev, Rashid A.; Magistretti, Pierre J.; Depeursinge, Christian; Juodkazis, Saulius; Rosen, Joseph; Anand, Vijayakumar
Indirect-imaging methods involve at least two steps, namely optical recording and computational reconstruction. The optical-recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object’s image corresponding to different spatial and spectral dimensions. There have been numerous optical-modulation functions and reconstruction methods developed in the past few years for different applications. In most cases, a compatible pair of the optical-modulation function and reconstruction method gives optimal performance. A new reconstruction method, termed nonlinear reconstruction (NLR), was developed in 2017 to reconstruct the object image in the case of optical-scattering modulators. Over the years, it has been revealed that the NLR can reconstruct an object’s image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR is investigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed
Valguse leviku numbriline modelleerimine murdumisnäitaja gradiendiga materjalistruktuurides
(Tartu Ülikool, 2013) Valdma, Sandhra-Mirella; Lukner, Heli, juhendaja; Tartu Ülikool. Loodus- ja tehnoloogiateaduskond; Tartu Ülikool. Füüsika instituut