A Multiresolution Algorithm for High-resolution Image Reconstruction PDF Download
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Author: Reuben Brasher
Publisher:
ISBN:
Category : Detectors
Languages : en
Pages : 80
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Book Description
Author: Reuben Brasher
Publisher:
ISBN:
Category : Detectors
Languages : en
Pages : 80
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Book Description
Author: Vivek Bannore
Publisher: Springer Science & Business Media
ISBN: 3642003842
Category : Mathematics
Languages : en
Pages : 121
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Book Description
To my wife, Mitu - Vivek Bannore Preface Preface In many imaging systems, under-sampling and aliasing occurs frequently leading to degradation of image quality. Due to the limited number of sensors available on the digital cameras, the quality of images captured is also limited. Factors such as optical or atmospheric blur and sensor noise can also contribute further to the d- radation of image quality. Super-Resolution is an image reconstruction technique that enhances a sequence of low-resolution images or video frames by increasing the spatial resolution of the images. Each of these low-resolution images contain only incomplete scene information and are geometrically warped, aliased, and - der-sampled. Super-resolution technique intelligently fuses the incomplete scene information from several consecutive low-resolution frames to reconstruct a hi- resolution representation of the original scene. In the last decade, with the advent of new technologies in both civil and mi- tary domain, more computer vision applications are being developed with a demand for high-quality high-resolution images. In fact, the demand for high- resolution images is exponentially increasing and the camera manufacturing te- nology is unable to cope up due to cost efficiency and other practical reasons.
Author: Thomas C. Pestak
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 83
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Book Description
There is a growing demand from numerous commercial and military applications for images with ever-improving spatial resolution. However, there are resolution-limiting factors inherent in all imaging systems. Decreasing pixel sizes and/or increasing sensor arrays are not always viable. Super-Resolution (SR) Image Reconstruction is an image processing technique that restores a high-resolution (HR) image from a series of low-resolution (LR) images of a particular scene. Recently, there has been extensive research on robust SR algorithms used for post-processing. The goal of this thesis is to explore the current SR research and design computationally efficient SR algorithms for real-time processing based on a non-uniform interpolation approach.
Author: A. Ravishankar Rao
Publisher: Artech House
ISBN: 1596932961
Category : Medical
Languages : en
Pages : 353
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Book Description
This innovative volume surveys the latest image acquisition advances in serial block face techniques in scanning electron microscopy, knife-edge scanning microscopy, and 4D imaging of multi-component biological systems. The book introduces parallel processing for biological applications. You learn advanced parallelization techniques for decomposing a problem domain and mapping it onto a parallel processing architecture using the message-passing interface (MPI) and OpenMP. Case studies show how these techniques have been successfully used in simulation tasks, data mining, and graphical visualization of biological datasets. You also find coverage of methods for developing scalable biological image databases and for facilitating greater interactive visualization of large image sets.
Author: Chiu-Chih Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Super-Resolution (SR) is a generic term, referring to a series of digital image processing techniques in which a high resolution (HR) image is reconstructed from a set of low resolution (LR) video frames or images. In other words, a HR image is obtained by integrating several LR frames captured from the same scene within a very short period of time. Constructing a SR image is a process that may require a lot of computational resources. To solve this problem, the SR reconstruction process involves 3 steps, namely image registration, degrading function estimation and image restoration. In this thesis, the fundamental process steps in SR image reconstruction algorithms are first introduced. Several known SR image reconstruction approaches are then discussed in detail. These SR reconstruction methods include: (1) traditional interpolation, (2) the frequency domain approach, (3) the inverse back-projection (IBP), (4) the conventional projections onto convex sets (POCS) and (5) regularized inverse optimization. Based on the analysis of some of the existing methods, a Wavelet-based POCS SR image reconstruction method is proposed. The new method is an extension of the conventional POCS method, that performs some convex projection operations in the Wavelet domain. The stochastic Wavelet coefficient refinement technique is used to adjust the Wavelet sub-image coefficients of the estimated HR image according to the stochastic F-distribution in order to eliminate the noisy or wrongly estimated pixels. The proposed SR method enhances the resulting quality of the reconstructed HR image, while retaining the simplicity of the conventional POCS method as well as increasing the convergence speed of POCS iterations. Simulation results show that the proposed Wavelet-based POCS iterative algorithm has led to some distinct features and performance improvement as compared to some of the SR approaches reviewed in this thesis.
Author: Tao Qian
Publisher: Springer Science & Business Media
ISBN: 376437778X
Category : Mathematics
Languages : en
Pages : 567
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Book Description
This volume reflects the latest developments in the area of wavelet analysis and its applications. Since the cornerstone lecture of Yves Meyer presented at the ICM 1990 in Kyoto, to some extent, wavelet analysis has often been said to be mainly an applied area. However, a significant percentage of contributions now are connected to theoretical mathematical areas, and the concept of wavelets continuously stretches across various disciplines of mathematics. Key topics: Approximation and Fourier Analysis Construction of Wavelets and Frame Theory Fractal and Multifractal Theory Wavelets in Numerical Analysis Time-Frequency Analysis Adaptive Representation of Nonlinear and Non-stationary Signals Applications, particularly in image processing Through the broad spectrum, ranging from pure and applied mathematics to real applications, the book will be most useful for researchers, engineers and developers alike.
Author: Manjunath V. Joshi
Publisher: Cambridge University Press
ISBN: 1108475124
Category : Computers
Languages : en
Pages : 255
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Book Description
Written using clear and accessible language, this useful guide discusses fundamental concepts and practices of multi-resolution image fusion.
Author: Phillip A. Laplante
Publisher: CRC Press
ISBN: 1351032720
Category : Technology & Engineering
Languages : en
Pages : 1890
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Book Description
The Encyclopedia of Image Processing presents a vast collection of well-written articles covering image processing fundamentals (e.g. color theory, fuzzy sets, cryptography) and applications (e.g. geographic information systems, traffic analysis, forgery detection). Image processing advances have enabled many applications in healthcare, avionics, robotics, natural resource discovery, and defense, which makes this text a key asset for both academic and industrial libraries and applied scientists and engineers working in any field that utilizes image processing. Written by experts from both academia and industry, it is structured using the ACM Computing Classification System (CCS) first published in 1988, but most recently updated in 2012.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 36
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Book Description
Some imaging sytems employ detector arrays which are not dense enough to meet the Nyquist criteria during image acquisition. This is particularly true for many staring infrared imagers. Thus, the full resolution afforded by the optics is not being realized in such a system. This paper presents a technique for estimating a high resolution image, with reduced aliasing, from a sequence of undersampled rotated and translationally shifted frames. Such an image sequence can can be obtained if an imager is mounted on a moving platform, such as an aircraft. Several approaches to this problem have been proposed in the literature. Here we extend some of this previous work. In particular, we define an observation model which incorporates accurate knowledge of the optical system. The high resolution image estimate is formed by minimizing a regularized cost function which is based on the observation model. We consider both gradient descent and conjugate gradient optimization procedures to minimize the cost function. We show that the conjugate gradient optimization provides rapid convergence. Detailed experimental results are provided to illustrate the performance of the proposed algorithm using both visible and infrared images.
Author: Ming Jiang
Publisher: Springer
ISBN: 3319916599
Category : Technology & Engineering
Languages : en
Pages : 421
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Book Description
This book collects a number of papers presented at the International Conference on Sensing and Imaging, which was held at Chengdu University of Information Technology on June 5-7, 2017. Sensing and imaging is an interdisciplinary field covering a variety of sciences and techniques such as optics, electricity, magnetism, heat, sound, mathematics, and computing technology. The field has diverse applications of interest such as sensing techniques, imaging, and image processing techniques. This book will appeal to professionals and researchers within the field.
