3,180 research outputs found
Digital Color Imaging
This paper surveys current technology and research in the area of digital
color imaging. In order to establish the background and lay down terminology,
fundamental concepts of color perception and measurement are first presented
us-ing vector-space notation and terminology. Present-day color recording and
reproduction systems are reviewed along with the common mathematical models
used for representing these devices. Algorithms for processing color images for
display and communication are surveyed, and a forecast of research trends is
attempted. An extensive bibliography is provided
Minimization of Halftone Noise in FLAT Regions for Improved Print Quality
The work in this thesis proposes a novel algorithm for enhancing the quality of flat regions in printed color image documents. The algorithm is designed to identify the flat regions based on certain criteria and filter these regions to minimize the noise prior and post Halftoning so as to make the hard copy look visibly pleasing. Noise prior to halftone process is removed using a spatial Gaussian filter together with a Hamming window, concluded from results after implementing various filtering techniques. A clustered dithering is applied in each channel of the image as Halftoning process. Furthermore, to minimize the post halftone noise, the halftone structure of the image is manipulated according to the neighboring sub-cells in their respective channels. This is done to reduce the brightness variation (a cause for noise) between the neighboring subcells. Experimental results show that the proposed algorithm efficiently minimizes noise in flat regions of mirumal gradient change in color images
Adaptive multi‐index collocation for uncertainty quantification and sensitivity analysis
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154316/1/nme6268.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154316/2/NME_6268_novelty.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154316/3/nme6268_am.pd
Geometric Surface Processing and Virtual Modeling
In this work we focus on two main topics "Geometric Surface Processing" and "Virtual Modeling". The inspiration and coordination for most of the research work contained in the thesis has been driven by the project New Interactive and Innovative Technologies for CAD (NIIT4CAD), funded by the European Eurostars Programme. NIIT4CAD has the ambitious aim of overcoming the limitations of the traditional approach to surface modeling of current 3D CAD systems by introducing new methodologies and technologies based on subdivision surfaces
in a new virtual modeling framework. These innovations will allow designers and engineers to transform quickly and intuitively an idea of shape in a high-quality geometrical model suited for engineering and manufacturing purposes.
One of the objective of the thesis is indeed the reconstruction and modeling of surfaces, representing arbitrary topology objects, starting from 3D irregular curve networks acquired through an ad-hoc smart-pen device.
The thesis is organized in two main parts: "Geometric Surface Processing" and "Virtual Modeling". During the development of the geometric pipeline in our Virtual Modeling system, we faced many challenges that captured our interest and opened new areas of research and experimentation.
In the first part, we present these theories and some applications to Geometric Surface Processing.
This allowed us to better formalize and give a broader understanding on some of the techniques used in our latest advancements on virtual modeling and surface reconstruction.
The research on both topics led to important results that have been published and presented in articles and conferences of international relevance
Improvements to the color quantization process
The presentation of color images on devices with limited color capabilities requires a reduction in the number of colors contained in the images. Color image quantization is the process of reducing the number of colors used in an image while maintaining its appearance as much as possible. This reduction is performed using a color image quantization algorithm. The quantization algorithm attempts to select k colors that best represent the contents of the image. The original image is then recolored using the representative colors. to improve the resulting image, a dithering process can be used in place of the recoloring.;This dissertation deals with several areas of the color image quantization process. The main objective, however, is new or improved algorithms for the production of images with a better visual quality than those produced by existing algorithms while maintaining approximately the same running time. First, a new algorithm is developed for the selection of the representative color set. The results produced by the new algorithm are better both visually and quantitatively when compared to existing algorithms. Second, a new nearest-neighbor search algorithm that is based on the Locally Sorted Search algorithm is developed to reduce the time required to map the input colors to a representative color. Finally, two modifications are made to the error-diffusion dithering technique that improve the execution time. These modifications include the use of a two-weight matrix for the distribution of the error values and the presentation of a method to parallelize the error-diffusion technique. Furthermore, the analytical results of several experiments are provided to show the effectiveness each of these additions and improvements
Biomimetic Design for Efficient Robotic Performance in Dynamic Aquatic Environments - Survey
This manuscript is a review over the published articles on edge detection. At first, it provides theoretical background, and then reviews wide range of methods of edge detection in different categorizes. The review also studies the relationship between categories, and presents evaluations regarding to their application, performance, and implementation. It was stated that the edge detection methods structurally are a combination of image smoothing and image differentiation plus a post-processing for edge labelling. The image smoothing involves filters that reduce the noise, regularize the numerical computation, and provide a parametric representation of the image that works as a mathematical microscope to analyze it in different scales and increase the accuracy and reliability of edge detection. The image differentiation provides information of intensity transition in the image that is necessary to represent the position and strength of the edges and their orientation. The edge labelling calls for post-processing to suppress the false edges, link the dispread ones, and produce a uniform contour of objects
Generalizing Reduction-Based Algebraic Multigrid
Algebraic Multigrid (AMG) methods are often robust and effective solvers for
solving the large and sparse linear systems that arise from discretized PDEs
and other problems, relying on heuristic graph algorithms to achieve their
performance. Reduction-based AMG (AMGr) algorithms attempt to formalize these
heuristics by providing two-level convergence bounds that depend concretely on
properties of the partitioning of the given matrix into its fine- and
coarse-grid degrees of freedom. MacLachlan and Saad (SISC 2007) proved that the
AMGr method yields provably robust two-level convergence for symmetric and
positive-definite matrices that are diagonally dominant, with a convergence
factor bounded as a function of a coarsening parameter. However, when applying
AMGr algorithms to matrices that are not diagonally dominant, not only do the
convergence factor bounds not hold, but measured performance is notably
degraded. Here, we present modifications to the classical AMGr algorithm that
improve its performance on matrices that are not diagonally dominant, making
use of strength of connection, sparse approximate inverse (SPAI) techniques,
and interpolation truncation and rescaling, to improve robustness while
maintaining control of the algorithmic costs. We present numerical results
demonstrating the robustness of this approach for both classical isotropic
diffusion problems and for non-diagonally dominant systems coming from
anisotropic diffusion
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