Deep Convolutional Neural Networks for Estimating Lens Distortion Parameters

In this paper we present a convolutional neural network (CNN) to predict multiple lens distortion parameters from a single input image. Unlike other methods, our network is suitable to create high resolution output as it directly estimates the parameters from the image which then can be used to rectify even very high resolution input images. As our method it is fully automatic, it is suitable for both casual creatives and professional artists. Our results show that our network accurately predicts the lens distortion parameters of high resolution images and corrects the distortions satisfactory

Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images

This work presents a novel deep-learning-based pipeline for the inverse problem of image deblurring, leveraging augmentation and pre-training with synthetic data. Our results build on our winning submission to the recent Helsinki Deblur Challenge 2021, whose goal was to explore the limits of state-of-the-art deblurring algorithms in a real-world data setting. The task of the challenge was to deblur out-of-focus images of random text, thereby in a downstream task, maximizing an optical-character-recognition-based score function. A key step of our solution is the data-driven estimation of the physical forward model describing the blur process. This enables a stream of synthetic data, generating pairs of ground-truth and blurry images on-the-fly, which is used for an extensive augmentation of the small amount of challenge data provided. The actual deblurring pipeline consists of an approximate inversion of the radial lens distortion (determined by the estimated forward model) and a U-Net architecture, which is trained end-to-end. Our algorithm was the only one passing the hardest challenge level, achieving over $70\%$ character recognition accuracy. Our findings are well in line with the paradigm of data-centric machine learning, and we demonstrate its effectiveness in the context of inverse problems. Apart from a detailed presentation of our methodology, we also analyze the importance of several design choices in a series of ablation studies. The code of our challenge submission is available under https://github.com/theophil-trippe/HDC_TUBerlin_version_1.Comment: This article has been published in a revised form in Inverse Problems and Imagin

Generation and Manipulation of Higher Order Fractional and Integer Bessel Gaussian Beams

Optical orbital angular momentum (OAM) describes orbiting photons, swirling local wave vectors, or spiraling phase distribution depending on what theory we use to explain light. If we consider light as a propagating electromagnetic wave, then light has the freedoms of frequency, magnitude, phase, and polarization. For a monochromatic light, expanding the later three freedoms spatiotemporally, numerous optical modes are solved from Maxwell’s equations and boundary conditions. OAM mode study starts from integer charge because it is in the integer form of the fundamental phase singularity structure. Fractional OAM mode is the Fourier series of integer OAM modes. The average OAM does not conserve along with propagation for the traditional fractional OAM modes. We propose a new asymmetric fractional Bessel Gaussian mode providing the average OAM conserving along with the propagation. To better understand the fractional OAM mode or integer OAM mode combination, we study the novel concentric vortex optics. The analytical propagation expression of the concentric vortex beam is derived and analyzed. The concentric vortex beam is essentially the OAM spectrum, with only two integer OAM components. The spectrum coefficiencies are real numbers and approximately power equalized in general cases. The concentric vortex beam is the coherent combination of incomplete Kummer beams. As the inner aperture tuning large, the beam evolves into the Kummer beam with the inner charge number. The aperture decreases, the outer charges Kummer beam dominates. The proposed asymmetric fractional Bessel Gaussian beam’s Fourier transform is azimuthal Gaussian perfect vortex. We use log-polar coordinate mapping diffractive optics to transform the elliptical Gaussian beam into the desired azimuthal Gaussian perfect vortex beam. The generated asymmetric fractional Bessel Gaussian beam is systematically compared with Kotlyar’s asymmetric Bessel Gaussian beam. It’s found that the proposed beam has a narrower OAM spectrum, preserving average fractional OAM. Furthermore, the log-polar transform’s inherent output lateral shifting problem is addressed for the first time to our knowledge. An improved log-polar design is proposed, and we use five critical metrics to show the new log-polar generated asymmetric Bessel Gaussian beam’s quality is much improved. The manipulation of the high order asymmetric fractional Bessel Gaussian beam is critical to applications scaling from communication, sensing, filamentation, to micromanipulation. We propose and demonstrate acousto-optical deflector (AOD) HOBBIT (Higher Order Bessel Beams Integrated in Time) system. The system can continuously tune the OAM modes on the order of 400 kHz. This speed beats the fastest spatial light modulator (SLM), and even better, the proposed system could work for high power applications

Orbital Angular Momentum Waves: Generation, Detection and Emerging Applications

Orbital angular momentum (OAM) has aroused a widespread interest in many fields, especially in telecommunications due to its potential for unleashing new capacity in the severely congested spectrum of commercial communication systems. Beams carrying OAM have a helical phase front and a field strength with a singularity along the axial center, which can be used for information transmission, imaging and particle manipulation. The number of orthogonal OAM modes in a single beam is theoretically infinite and each mode is an element of a complete orthogonal basis that can be employed for multiplexing different signals, thus greatly improving the spectrum efficiency. In this paper, we comprehensively summarize and compare the methods for generation and detection of optical OAM, radio OAM and acoustic OAM. Then, we represent the applications and technical challenges of OAM in communications, including free-space optical communications, optical fiber communications, radio communications and acoustic communications. To complete our survey, we also discuss the state of art of particle manipulation and target imaging with OAM beams

Алгоритми компенсації оптичних спотворень на цифрових зображеннях

До бакалаврської дипломної роботи Перцова Вадим Миколайовича. На тему: «Алгоритми компенсації оптичних спотворень на цифрових зображеннях» Дана дипломна робота присвячена методам компенсації оптичних спотворень на цифрових зображеннях. В роботі зроблено аналіз алгоритмів компенсації оптичних спотворень та визначення найбільш оптимальних методів компенсації для цифрових зображеннях. Аналіз проводиться в пакеті прикладних програм MATLAB.This thesis is devoted to algorithms for compensating optical distortion of digital images. The paper analyzes the methods of optical distortion compensation and determines the most optimal compensation methods for digital images. The analysis is performed in the MATLAB application package

Metaoptics for Spectral and Spatial Beam Manipulation

Laser beam combining and beam shaping are two important areas with applications in optical communications, high power lasers, and atmospheric propagation studies. In this dissertation, metaoptical elements have been developed for spectral and spatial beam shaping, and multiplexing. Beams carrying orbital angular momentum (OAM), referred to as optical vortices, have unique propagation properties. Optical vortex beams carrying different topological charges are orthogonal to each other and have low inter-modal crosstalk which allows for them to be (de)multiplexed. Efficient spatial (de)multiplexing of these beams have been carried out by using diffractive optical geometrical coordinate transformation elements. The spatial beam combining technique shown here is advantageous because the efficiency of the system is not dependent on the number of OAM states being combined. The system is capable of generating coaxially propagating beams in the far-field and the beams generated can either be incoherently or coherently multiplexed with applications in power scaling and dynamic intensity profile manipulations. Spectral beam combining can also be achieved with the coordinate transformation elements. The different wavelengths emitted by fiber sources can be spatially overlapped in the far-field plane and the generated beams are Bessel-Gauss in nature with enhanced depth of focus properties. Unique system responses and beam shapes in the far-field can be realized by controlling amplitude, phase, and polarization at the micro-scale. This has been achieved by spatially varying the structural parameters at the subwavelength scale and is analogous to local modification of material properties. With advancements in fabrication technology, it is possible to control not just the lithographic process, but also the deposition process. In this work, a unique combination of spatial structure variations in conjunction with the conformal coating properties of an atomic layer deposition tool has been utilized to create metal-oxide nano-hair structures that are compatible with high power laser systems. These devices are multifunctional – acting as resonant structures for one wavelength regime and as effective index structures in a different wavelength regime. Discrete and continuous phase functions have been realized with this controlled fabrication process. The design, simulation, fabrication and experimental characterization of these optical elements are presented

Automatic Detection of Calibration Grids in Time-of-Flight Images

It is convenient to calibrate time-of-flight cameras by established methods, using images of a chequerboard pattern. The low resolution of the amplitude image, however, makes it difficult to detect the board reliably. Heuristic detection methods, based on connected image-components, perform very poorly on this data. An alternative, geometrically-principled method is introduced here, based on the Hough transform. The projection of a chequerboard is represented by two pencils of lines, which are identified as oriented clusters in the gradient-data of the image. A projective Hough transform is applied to each of the two clusters, in axis-aligned coordinates. The range of each transform is properly bounded, because the corresponding gradient vectors are approximately parallel. Each of the two transforms contains a series of collinear peaks; one for every line in the given pencil. This pattern is easily detected, by sweeping a dual line through the transform. The proposed Hough-based method is compared to the standard OpenCV detection routine, by application to several hundred time-of-flight images. It is shown that the new method detects significantly more calibration boards, over a greater variety of poses, without any overall loss of accuracy. This conclusion is based on an analysis of both geometric and photometric error.Comment: 11 pages, 11 figures, 1 tabl