Browsing by Author "Praveen, Periyasamy Angamuthu"

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Implementation of a Large-Area Diffractive Lens Using Multiple Sub-Aperture Diffractive Lenses and Computational Reconstruction
(Licensee MDPI, 2022) Gopinath, Shivasubramanian; Praveen, Periyasamy Angamuthu; Kahro, Tauno; Bleahu, Andrei-Ioan; Arockiaraj, Francis Gracy; Smith, Daniel; Ng, Soon Hock; Juodkazis, Saulius; Kukli, Kaupo; Tamm, Aile; Anand, Vijayakumar
Direct imaging systems that create an image of an object directly on the sensor in a single step are prone to many constraints, as a perfect image is required to be recorded within this step. In designing high resolution direct imaging systems with a diffractive lens, the outermost zone width either reaches the lithography limit or the diffraction limit itself, imposing challenges in fabrication. However, if the imaging mode is switched to an indirect one consisting of multiple steps to complete imaging, then different possibilities open. One such method is the widely used indirect imaging method with Golay configuration telescopes. In this study, a Golay-like configuration has been adapted to realize a large-area diffractive lens with three sub-aperture diffractive lenses. The sub-aperture diffractive lenses are not required to collect light and focus them to a single point as in a direct imaging system, but to focus independently on different points within the sensor area. This approach of a Large-Area Diffractive lens with Integrated Sub-Apertures (LADISA) relaxes the fabrication constraints and allows the sub-aperture diffractive elements to have a larger outermost zone width and a smaller area. The diffractive sub-apertures were manufactured using photolithography. The fabricated diffractive element was implemented in indirect imaging mode using non-linear reconstruction and the Lucy–Richardson–Rosen algorithm with synthesized point spread functions. The computational optical experiments revealed improved optical and computational imaging resolutions compared to previous studies.
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
Single Shot Lensless Interferenceless Phase Imaging of Biochemical Samples Using Synchrotron near Infrared Beam
(Licensee MDPI, 2022) Han, Molong; Smith, Daniel; Ng, Soon Hock; Katkus, Tomas; Rajeswary, Aravind Simon John Francis; Praveen, Periyasamy Angamuthu; Bambery, Keith R.; Tobin, Mark J.; Vongsvivut, Jitraporn; Juodkazis, Saulius; Anand, Vijayakumar
Phase imaging of biochemical samples has been demonstrated for the first time at the Infrared Microspectroscopy (IRM) beamline of the Australian Synchrotron using the usually discarded near-IR (NIR) region of the synchrotron-IR beam. The synchrotron-IR beam at the Australian Synchrotron IRM beamline has a unique fork shaped intensity distribution as a result of the gold coated extraction mirror shape, which includes a central slit for rejection of the intense X-ray beam. The resulting beam configuration makes any imaging task challenging. For intensity imaging, the fork shaped beam is usually tightly focused to a point on the sample plane followed by a pixel-by-pixel scanning approach to record the image. In this study, a pinhole was aligned with one of the lobes of the fork shaped beam and the Airy diffraction pattern was used to illuminate biochemical samples. The diffracted light from the samples was captured using a NIR sensitive lensless camera. A rapid phase-retrieval algorithm was applied to the recorded intensity distributions to reconstruct the phase information. The preliminary results are promising to develop multimodal imaging capabilities at the IRM beamline of the Australian Synchrotron.
Three-dimensional phase imaging with near infrared synchrotron beam using phase-retrieval algorithm
(2023) Han, Molong; Anand, Vijayakumar; Juodkazis, Saulius; Vongsvivut, Jitraporn; Tobin, Mark J.; Praveen, Periyasamy Angamuthu; Rajeswary, Aravind Simon John Francis; Katkus, Tomas A.; Ng, Soon Hock; Smith, Daniel