Using complex light modulation for holographic applications

Complex light modulation is the ability to control a light-wave’s phase and amplitude, thereby allowing complete control of the light-wave at any spatial location. The applied optics group at The University of Texas at Austin Electrical and Computer Engineering Department created a fully complex hologram by a combination of spatial light modulators. A digital micromirror device (DMD) was used to produce a precise amplitude profile, and a liquid crystal spatial light modulator (SLM) was used to produce the phase profile. A band-limited 4-f imaging system imaged the DMD onto the SLM to create a fully complex modulated wavefront, which reconstructed a holographic image at the desired location. With this capability, it is possible to create improved imaging methods for the consumer, medical, and defense industries as well as applications in holography. Our previous research has successfully created phase-only holograms (POH), amplitude-only beam-shaping patterns, and published simulation results on full-complex modulation. This thesis provides an in-depth experimental analysis of the full-complex hologram.Electrical and Computer Engineerin

An importance driven genetic algorithm for the halftoning process

Most evolutionary approaches to halftoning techniques have been concerned with the paramount goal of halftoning: achieving an accurate reproduction of local grayscale intensities while avoiding the introduction of artifacts. A secondary concern in halftoning has been the preservation of edges in the halftoned image. In this paper, we will introduce a new evolutionary approach through the use of an importance function. This approach has at least two main characteristics. First, it can produce results similar to many other halftoning techniques. Second, if the chosen importance function is accordingly changed, areas of the image with high variance can be highlighted.III Workshop de Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI

Variational tetrahedral meshing

In this paper, a novel Delaunay-based variational approach to isotropic tetrahedral meshing is presented. To achieve both robustness and efficiency, we minimize a simple mesh-dependent energy through global updates of both vertex positions and connectivity. As this energy is known to be the ∠1 distance between an isotropic quadratic function and its linear interpolation on the mesh, our minimization procedure generates well-shaped tetrahedra. Mesh design is controlled through a gradation smoothness parameter and selection of the desired number of vertices. We provide the foundations of our approach by explaining both the underlying variational principle and its geometric interpretation. We demonstrate the quality of the resulting meshes through a series of examples

Dithering by Differences of Convex Functions

Motivated by a recent halftoning method which is based on electrostatic principles, we analyse a halftoning framework where one minimizes a functional consisting of the difference of two convex functions (DC). One of them describes attracting forces caused by the image gray values, the other one enforces repulsion between points. In one dimension, the minimizers of our functional can be computed analytically and have the following desired properties: the points are pairwise distinct, lie within the image frame and can be placed at grid points. In the two-dimensional setting, we prove some useful properties of our functional like its coercivity and suggest to compute a minimizer by a forward-backward splitting algorithm. We show that the sequence produced by such an algorithm converges to a critical point of our functional. Furthermore, we suggest to compute the special sums occurring in each iteration step by a fast summation technique based on the fast Fourier transform at non-equispaced knots which requires only Ο(m log(m)) arithmetic operations for m points. Finally, we present numerical results showing the excellent performance of our DC dithering method

Efficient Halftoning via Deep Reinforcement Learning

Halftoning aims to reproduce a continuous-tone image with pixels whose intensities are constrained to two discrete levels. This technique has been deployed on every printer, and the majority of them adopt fast methods (e.g., ordered dithering, error diffusion) that fail to render structural details, which determine halftone's quality. Other prior methods of pursuing visual pleasure by searching for the optimal halftone solution, on the contrary, suffer from their high computational cost. In this paper, we propose a fast and structure-aware halftoning method via a data-driven approach. Specifically, we formulate halftoning as a reinforcement learning problem, in which each binary pixel's value is regarded as an action chosen by a virtual agent with a shared fully convolutional neural network (CNN) policy. In the offline phase, an effective gradient estimator is utilized to train the agents in producing high-quality halftones in one action step. Then, halftones can be generated online by one fast CNN inference. Besides, we propose a novel anisotropy suppressing loss function, which brings the desirable blue-noise property. Finally, we find that optimizing SSIM could result in holes in flat areas, which can be avoided by weighting the metric with the contone's contrast map. Experiments show that our framework can effectively train a light-weight CNN, which is 15x faster than previous structure-aware methods, to generate blue-noise halftones with satisfactory visual quality. We also present a prototype of deep multitoning to demonstrate the extensibility of our method

An importance driven genetic algorithm for the halftoning process

Most evolutionary approaches to halftoning techniques have been concerned with the paramount goal of halftoning: achieving an accurate reproduction of local grayscale intensities while avoiding the introduction of artifacts. A secondary concern in halftoning has been the preservation of edges in the halftoned image. In this paper, we will introduce a new evolutionary approach through the use of an importance function. This approach has at least two main characteristics. First, it can produce results similar to many other halftoning techniques. Second, if the chosen importance function is accordingly changed, areas of the image with high variance can be highlighted.III Workshop de Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI

Échantillonnage basé sur les Tuiles de Penrose et applications en infographie

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal