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

Permanent URI for this collectionhttps://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.

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Coded Aperture-Based Self-wavefront Interference Using Transverse Splitting Holography
(2023 International Conference on Next Generation Electronics (NEleX), 2023) Joshi, Narmada; Xavier, Agnes Pristy Ignatius; Arockiaraj, Francis Gracy; Rajeswary, Aravind Simon John Francis; Juodkazis, Saulius; Rosen, Joseph; Tamm, Aile; Anand, Vijayakumar
Self-wavefront interference transverse splitting holography (SWITSH) is a recently developed holographic technique to solve a fundamental problem in the manufacturing of large-area diffractive lenses. In SWITSH, a low NA diffractive lens modulates the light from an object, and the modulated light is interfered with light from the same object that reaches beyond the aperture of the diffractive lens. The resulting self-interference hologram is processed with the pre-recorded point spread hologram using the Lucy-Richardson-Rosen algorithm. Since the self-interference hologram is formed by collecting light beyond the NA of the diffractive lens, it acquires the object information corresponding to the higher spatial frequencies of the object. Consequently, a higher imaging resolution is obtained in SWITSH compared to that of direct imaging with a diffractive lens. In the proof-of-concept study, a resolution improvement of an order was demonstrated. However, the optical architecture of the first version of SWITSH was not optimal, as the strength of the self-interference signal was weak. In this study, we improve SWITSH using different coded apertures, such as axicon and spiral element. An improvement in the strength of the self-interference signal was noticed with the axicon and spiral element. Simulation and experimental results using a diffractive lens, axicon and spiral element are presented.
Computational Imaging Using Deterministic Optical Fields and Non-linear Reconstruction
(Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), 2022) Arockiaraj, Francis Gracy; Selva, Shakina Jothi; Inbanathan, Stephen Rajkumar; Kamalam, Manueldoss Beaula Ruby; Rajeswary, Aravind Simon John Francis; Anand, Vijayakumar; Rosen, Joseph
Computational imaging techniques are indirect ones consisting of two steps: optical recording and computational reconstruction. In this study, deterministic optical fields such as Bessel, Airy, Gaussian and Laguerre-Gaussian were studied in this indirect imaging framework.
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.
Faithful Transfer of 3D Propagation Characteristics of Deterministic and Random Optical Fields to Coded Aperture Imaging Systems Using Lucy-Richardson-Rosen Algorithm
(2023 International Conference on Next Generation Electronics (NEleX), 2023) Xavier, Agnes Pristy Ignatius; Arockiaraj, Francis Gracy; Gopinath, Shivasubramanian; Rajeswary, Aravind Simon John Francis; Reddy, Andra Naresh Kumar; Ganeev, Rashid A.; Singh, M. Scott Arockia; Tania, S.D. Milling; Anand, Vijayakumar
Engineering the complex amplitude and polarization of light is essential for various applications. In this direction, many deterministic and random optical beams such as Airy Bessel, and self-rotating beams were developed. While the above beams satisfied the requirements for the targeted applications, they are not suitable for imaging applications in spite of the valuable axial characteristics they possess, as they are not effective object-image mapping elements. Consequently, when exotic beams were implemented for direct imaging, only a distorted image was obtained. However, the scenario is different in coded aperture imaging (CAI) methods, where the imaging mode is indirect, consisting of optical recording and computational image recovery. Therefore, the point spread function (PSF) in CAI is not the recorded intensity distribution but the reconstructed intensity distribution. By employing a suitable computational reconstruction method, it is possible to convert the recorded intensity distribution into a Delta-like function. In this study, Lucy-Richardson-Rosen algorithm has been implemented as a generalized image recovery method for a wide range of optical beams, and the performance is validated in both simulation and optical experiments.
Fresnel incoherent correlation holography with Lucy-Richardson-Rosen algorithm and modified Gerchberg-Saxton algorithm
(2023) Anand, Vijayakumar; Juodkazis, Saulius; Rajeswary, Aravind Simon John Francis; Arockiaraj, Francis Gracy; Gopinath, Shivasubramanian; Bleahu, Andrei
Fresnel incoherent correlation holography with Lucy-Richardson-Rosen algorithm and modified Gerchberg-Saxton algorithm
(Society of Photo-Optical Instrumentation Engineers (SPIE), 2023) Bleahu, Andrei; Gopinath, Shivasubramanian; Arockiaraj, Francis Gracy; Rajeswary, Aravind Simon John Francis; Juodkazis, Saulius
Holographic solution to a fundamental problem in diffractive optics: resolution beyond diffraction and lithography limits
(2023) Bleahu, Andrei; Gopinath, Shivasubramanian; Xavier, Agnes Pristy Ignatius; Kahro, Tauno; Reddy, Andra Naresh Kumar; Arockiaraj, Francis Gracy; Smith, Daniel; Ng, Soon Hock; Katkus, Tomas; Rajeswary, Aravind Simon John Francis; Angamuthu, Praveen Periyasami; Pikker, Siim; Kukli, Kaupo; Tamm, Aile; Juodkazis, Saulius; Rosen, Joseph; Anand, Vijayakumar
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.
Implementation of a Large-Area Diffractive Lens Using Multiple Sub-Aperture Diffractive Lenses and Computational Reconstruction
(2023) Gopinath, Shivasubramanian; Angamuthu, Praveen Periysamy; Kahro, Tauno; Bleahu, Andrei; Arockiaraj, Francis Gracy; Smith, Daniel; Hock Ng, Soon; 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.
Improved Classification of Blurred Images with Deep-Learning Networks Using Lucy-Richardson-Rosen Algorithm
(Licensee MDPI, 2023) Jayavel, Amudhavel; Gopinath, Shivasubramanian; Angamuthu, Praveen Periyasamy; Arockiaraj, Francis Gracy; Bleahu, Andrei; Xavier, Agnes Pristy Ignatius; Smith, Daniel; Han, Molong; Slobozhan, Ivan; Ng, Soon Hock; Katkus, Tomas; Rajeswary, Aravind Simon John Francis; Sharma, Rajesh; Juodkazis, Saulius; Anand, Vijayakumar
Pattern recognition techniques form the heart of most, if not all, incoherent linear shift-invariant systems. When an object is recorded using a camera, the object information is sampled by the point spread function (PSF) of the system, replacing every object point with the PSF in the sensor. The PSF is a sharp Kronecker Delta-like function when the numerical aperture (NA) is large with no aberrations. When the NA is small, and the system has aberrations, the PSF appears blurred. In the case of aberrations, if the PSF is known, then the blurred object image can be deblurred by scanning the PSF over the recorded object intensity pattern and looking for pattern matching conditions through a mathematical process called correlation. Deep learning-based image classification for computer vision applications gained attention in recent years. The classification probability is highly dependent on the quality of images as even a minor blur can significantly alter the image classification results. In this study, a recently developed deblurring method, the Lucy-Richardson-Rosen algorithm (LR2A), was implemented to computationally refocus images recorded in the presence of spatio-spectral aberrations. The performance of LR2A was compared against the parent techniques: Lucy-Richardson algorithm and non-linear reconstruction. LR2A exhibited a superior deblurring capability even in extreme cases of spatio-spectral aberrations. Experimental results of deblurring a picture recorded using high-resolution smartphone cameras are presented. LR2A was implemented to significantly improve the performances of the widely used deep convolutional neural networks for image classification.
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
Optimizing the temporal and spatial resolutions and light throughput of Fresnel incoherent correlation holography in the framework of coded aperture imaging
(2024) Arockiaraj, Francis Gracy; Xavier, Agnes Pristy Ignatius; Gopinath, Shivasubramanian; Rajeswary, Aravind Simon John Francis; Juodkazis, Saulius; Anand, Vijayakumar
Fresnel incoherent correlation holography (FINCH) is a well-established digital holography technique for 3D imaging of objects illuminated by spatially incoherent light. FINCH has a higher lateral resolution of 1.5 times that of direct imaging systems with the same numerical aperture. However, the other imaging characteristics of FINCH, such as axial resolution, temporal resolution, light throughput, and signal-to-noise ratio (SNR), are lower than those of direct imaging systems. Different techniques were developed by researchers around the world to improve the imaging characteristics of FINCH while retaining the inherent higher lateral resolution of FINCH. However, most of the solutions developed to improve FINCH presented additional challenges. In this study, we optimized FINCH in the framework of coded aperture imaging. Two recently developed computational methods, such as transport of amplitude into phase based on the Gerchberg Saxton algorithm and Lucy–Richardson–Rosen algorithm, were applied to improve light throughput and image reconstruction, respectively. The above implementation improved the axial resolution, temporal resolution, and SNR of FINCH and moved them closer to those of direct imaging while retaining the high lateral resolution. A point spread function (PSF) engineering technique has been implemented to prevent the low lateral resolution problem associated with the PSF recorded using pinholes with a large diameter. We believe that the above developments are beyond the state-of-the-art of existing FINCH-scopes.
Realizing Fresnel Incoherent Correlation Holography as a Coded Aperture Imaging System using Advanced Computational Algorithms
(2023) Arockiaraj, Francis Gracy; Xavier, Agnes Pristy Ignatius; Gopinath, Shivasubramanian; Rajeswary, Aravind Simon John Francis; Juodkazis, Saulius; Anand, Vijayakumar
Fresnel incoherent correlation holography (FINCH) also called as incoherent digital holography. In FINCH, a self-interference Fresnel hologram is created when light from an object point is split into two, modulated using two different quadratic phase masks and interfered. At least three such holograms are needed with phase shifts 0,2π/3 and 4π/3 and combined to remove the twin image and bias terms during computational reconstruction involving Fresnel backpropagation. When the FINCH setup is engineered to achieve the same beam diameter for the two interfering beams, a super lateral resolution which is 1.5 times that of a direct imaging system for the same numerical aperture, is obtained. FINCH has a low temporal and axial resolution and low light throughput when compared to the direct imaging system. In this study, FINCH is enhanced and realized as a coded aperture imaging (CAI) system using three computational algorithms: Transport of Amplitude into Phase based on Gerchberg Saxton Algorithm (TAP-GSA), Lucy-Richardson-Rosen algorithm (LRRA) and computational point spread function engineering (CPSFE) technique. The PSF is recorded for FINCH in the first step as in CAI and used as the reconstruction function. The TAP-GSA was used to improve the design of phase masks and achieve a high light throughput. The CPSFE was used to shift the lateral resolution limit from the diameter of the pinhole which is used for recording the PSF to the limit of FINCH. The LRRA was used for the reconstruction of FINCH holograms. Optical experimental results of CAI-inspired ‘perfect’ FINCH are promising for applications in fluorescence microscopy.
Realizing large-area diffractive lens using multiple subaperture diffractive lenses and computational reconstruction
(2023) Gopinath, Shivasubramanian; Xavier, Agnes Pristy Ignatius; Angamuthu, Praveen Periyasamy; Kahro, Tauno; Tamm, Oskar; Bleahu, Andrei; Arockiaraj, Francis Gracy; Smith, Daniel; Ng, Soon Hock; Juodkazis, Saulius; Kukli, Kaupo; Tamm, Aile; Anand, Vijayakumar
Roadmap on computational methods in optical imaging and holography [invited].
(2024) Rosen, Joseph; Alford, Simon; Allan, Blake; Anand, Vijayakumar; Arnon, Shlomi; Arockiaraj, Francis Gracy; Art, Jonathan; Bai, Bijie; Balasubramaniam, Ganesh M.; Birnbaum, Tobias; Bisht, Nandan S.; Blinder, David; Cao, Liangcai; Chen, Qian; Chen, Ziyang; Dubey, Vishesh; Egiazarian, Karen; Ercan, Mert; Forbes, Andrew; Gopakumar, G.; Gao, Yunhui; Gigan, Sylvain; Gocłowski, Paweł; Gopinath, Shivasubramanian; Greenbaum, Alon; Horisaki, Ryoichi; Ierodiaconou, Daniel; Juodkazis, Saulius; Karmakar, Tanushree; Katkovnik, Vladimir; Khonina, Svetlana N.; Kner, Peter; Kravets, Vladislav; Kumar, Ravi; Lai, Yingming; Li, Chen; Li, Jiaji; Li, Shaoheng; Li, Yuzhu; Liang, Jinyang; Manavalan, Gokul; Mandal, Aditya Chandra; Manisha, Manisha; Mann, Christopher; Marzejon, Marcin J.; Moodley, Chané; Morikawa, Junko; Muniraj, Inbarasan; Narbutis, Donatas; Ng, Soon Hock; Nothlawala, Fazilah; Oh, Jeonghun; Ozcan, Aydogan; Park, YongKeun; Porfirev, Alexey P.; Potcoava, Mariana; Prabhakar, Shashi; Pu, Jixiong; Rai, Mani Ratnam; Rogalski, Mikołaj; Ryu, Meguya; Choudhary, Sakshi; Salla, Gangi Reddy; Schelkens, Peter; Şener, Sarp Feykun; Shevkunov, Igor; Shimobaba, Tomoyoshi; Singh, Rakesh K.; Singh, Ravindra P.; Stern, Adrian; Sun, Jiasong; Zhou, Shun; Zuo, Chao; Zurawski, Zack; Tahara, Tatsuki; Tiwari, Vipin; Trusiak, Maciej; Vinu, R. V.; Volotovskiy, Sergey G.; Yılmaz, Hasan; Barbosa De Aguiar, Hilton; Ahluwalia, Balpreet S.; Ahmad, Azeem
Computational methods have been established as cornerstones in optical imaging and holography in recent years. Every year, the dependence of optical imaging and holography on computational methods is increasing significantly to the extent that optical methods and components are being completely and efficiently replaced with computational methods at low cost. This roadmap reviews the current scenario in four major areas namely incoherent digital holography, quantitative phase imaging, imaging through scattering layers, and super-resolution imaging. In addition to registering the perspectives of the modern-day architects of the above research areas, the roadmap also reports some of the latest studies on the topic. Computational codes and pseudocodes are presented for computational methods in a plug-and-play fashion for readers to not only read and understand but also practice the latest algorithms with their data. We believe that this roadmap will be a valuable tool for analyzing the current trends in computational methods to predict and prepare the future of computational methods in optical imaging and holography.
Single-Shot 3D Incoherent Imaging Using Deterministic and Random Optical Fields with Lucy–Richardson–Rosen Algorithm
(2023) Xavier, Agnes Pristy Ignatius; Arockiaraj, Francis Gracy; Gopinath, Shivasubramanian; Rajeswary, Aravind Simon John Francis; Reddy, Andra Naresh Kumar; Ganeev, Rashid A.; Singh, M. Scott Arockia; Tania, S. D. Milling; Anand, Vijayakumar
Coded aperture 3D imaging techniques have been rapidly evolving in recent years. The two main directions of evolution are in aperture engineering to generate the optimal optical field and in the development of a computational reconstruction method to reconstruct the object’s image from the intensity distribution with minimal noise. The goal is to find the ideal aperture–reconstruction method pair, and if not that, to optimize one to match the other for designing an imaging system with the required 3D imaging characteristics. The Lucy–Richardson–Rosen algorithm (LR2A), a recently developed computational reconstruction method, was found to perform better than its predecessors, such as matched filter, inverse filter, phase-only filter, Lucy–Richardson algorithm, and non-linear reconstruction (NLR), for certain apertures when the point spread function (PSF) is a real and symmetric function. For other cases of PSF, NLR performed better than the rest of the methods. In this tutorial, LR2A has been presented as a generalized approach for any optical field when the PSF is known along with MATLAB codes for reconstruction. The common problems and pitfalls in using LR2A have been discussed. Simulation and experimental studies for common optical fields such as spherical, Bessel, vortex beams, and exotic optical fields such as Airy, scattered, and self-rotating beams have been presented. From this study, it can be seen that it is possible to transfer the 3D imaging characteristics from non-imaging-type exotic fields to indirect imaging systems faithfully using LR2A. The application of LR2A to medical images such as colonoscopy images and cone beam computed tomography images with synthetic PSF has been demonstrated. We believe that the tutorial will provide a deeper understanding of computational reconstruction using LR2A.

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