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Author: Bartus Michael Byerley
Publisher:
ISBN:
Category :
Languages : en
Pages : 286
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Book Description
Author: Bartus Michael Byerley
Publisher:
ISBN:
Category :
Languages : en
Pages : 286
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Book Description
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: David Capel
Publisher: Springer Science & Business Media
ISBN: 0857293842
Category : Computers
Languages : en
Pages : 233
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Book Description
This book investigates sets of images consisting of many overlapping viewsofa scene, and how the information contained within them may be combined to produce single images of superior quality. The generic name for such techniques is frame fusion. Using frame fusion, it is possible to extend the fieldof view beyond that ofany single image, to reduce noise, to restore high-frequency content, and even to increase spatial resolution and dynamic range. The aim in this book is to develop efficient, robust and automated frame fusion algorithms which may be applied to real image sequences. An essential step required to enable frame fusion is image registration: computing the point-to-point mapping between images in their overlapping region. This sub problem is considered in detail, and a robust and efficient solution is proposed and its accuracy evaluated. Two forms of frame fusion are then considered: image mosaic ing and super-resolution. Image mosaicing is the alignment of multiple images into a large composition which represents part of a 3D scene. Super-resolution is a more sophisticated technique which aims to restore poor-quality video sequences by mod elling and removing the degradations inherent in the imaging process, such as noise, blur and spatial-sampling. A key element in this book is the assumption of a completely uncalibrated cam era. No prior knowledge of the camera parameters, its motion, optics or photometric characteristics is assumed. The power of the methods is illustrated with many real image sequence examples.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 71
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Book Description
This thesis digital image Super-Resolution techniques using the Expectation Maximization (EM) and Maximum a posteriori (MAP) techniques are discussed. A Super-resolution algorithm using the EM algorithm in the frequency domain taking advantage of the diagonalization property of the DFT is discussed. Super-resolution using a combination of EM and MAP algorithms is also presented. We have considered the problem of obtaining a high resolution (HR) image from multiple low resolution (LR) frames. For this approach, the low resolution frames are required to have sub-pixel shifts among them, thus making each low resolution frame provide unique information about the scene which can be used to construct a high resolution frame. A method for interlacing the multiple LR frames to form a high resolution grid is discussed. This approach reduces the complexity of the super-resolution algorithm and provides for efficient implementation in the frequency domain. Point spread function (PSF) estimation, which is critical to the quality of the final image is also discussed. The practical scenario in which the PSF is partially known is considered. The image observation model accounts for blurring due to PSF and subsampling. In addition, the LR frames are assumed to be corrupted by additive white Gaussian noise (AWGN) whose variance is estimated by the algorithm. The super-resolution algorithm is applied to synthetic data as well as real data. Given a set of LR frames the algorithm forms a HR grid and performs image restoration on the HR grid to yield an image with higher pixel density. Experimental results are presented and conclusions are drawn.
Author: Jordi Salvador
Publisher: Academic Press
ISBN: 0081011350
Category : Computers
Languages : en
Pages : 164
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Book Description
Example-Based Super Resolution provides a thorough introduction and overview of example-based super resolution, covering the most successful algorithmic approaches and theories behind them with implementation insights. It also describes current challenges and explores future trends. Readers of this book will be able to understand the latest natural image patch statistical models and the performance limits of example-based super resolution algorithms, select the best state-of-the-art algorithmic alternative and tune it for specific use cases, and quickly put into practice implementations of the latest and most successful example-based super-resolution methods. - Provides detailed coverage of techniques and implementation details that have been successfully introduced in diverse and demanding real-world applications - Covers a wide variety of machine learning approaches, ranging from cross-scale self-similarity concepts and sparse coding, to the latest advances in deep learning - Presents a statistical interpretation of the subspace of natural image patches that transcends super resolution and makes it a valuable source for any researcher on image processing or low-level vision
Author: Raunaq Singh Kainth
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Super resolution image can be obtained from combining several low resolution noisy and blurred images. We propose an efficient algorithm to produce super resolution microscopic images. In the proposed algorithm, accurate sub-pixel motion between images is essential for reconstructing the image. Denoising is carried initially by adjusting the low resolution images. Shift fusion approach is applied to enhance the resolution of image and improved optical flow method is used for registration of images. The proposed method is applied to each color channel separately. The results are tested with synthetic downgraded images, popular low resolution datasets and experimental real-life images showing significant improvement in quality of images, with considerable less time cost and memory consumption than those of existing methods. Qualitative analysis is studied through edge detection method and observing visible features. Quantitative analysis is inspected showing improvement in resolution by measuring observable minimum distance.
Author: Peyman Milanfar
Publisher: CRC Press
ISBN: 135183388X
Category : Computers
Languages : en
Pages : 521
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Book Description
With the exponential increase in computing power and broad proliferation of digital cameras, super-resolution imaging is poised to become the next "killer app." The growing interest in this technology has manifested itself in an explosion of literature on the subject. Super-Resolution Imaging consolidates key recent research contributions from eminent scholars and practitioners in this area and serves as a starting point for exploration into the state of the art in the field. It describes the latest in both theoretical and practical aspects of direct relevance to academia and industry, providing a base of understanding for future progress. Features downloadable tools to supplement material found in the book Recent advances in camera sensor technology have led to an increasingly larger number of pixels being crammed into ever-smaller spaces. This has resulted in an overall decline in the visual quality of recorded content, necessitating improvement of images through the use of post-processing. Providing a snapshot of the cutting edge in super-resolution imaging, this book focuses on methods and techniques to improve images and video beyond the capabilities of the sensors that acquired them. It covers: History and future directions of super-resolution imaging Locally adaptive processing methods versus globally optimal methods Modern techniques for motion estimation How to integrate robustness Bayesian statistical approaches Learning-based methods Applications in remote sensing and medicine Practical implementations and commercial products based on super-resolution The book concludes by concentrating on multidisciplinary applications of super-resolution for a variety of fields. It covers a wide range of super-resolution imaging implementation techniques, including variational, feature-based, multi-channel, learning-based, locally adaptive, and nonparametric methods. This versatile book can be used as the basis for short courses for engineers and scientists, or as part of graduate-level courses in image processing.
Author: Subhasis Chaudhuri
Publisher: Springer Science & Business Media
ISBN: 0792374711
Category : Computers
Languages : en
Pages : 287
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Book Description
Super-Resolution Imaging serves as an essential reference for both academicians and practicing engineers. It can be used both as a text for advanced courses in imaging and as a desk reference for those working in multimedia, electrical engineering, computer science, and mathematics. The first book to cover the new research area of super-resolution imaging, this text includes work on the following groundbreaking topics: Image zooming based on wavelets and generalized interpolation; Super-resolution from sub-pixel shifts; Use of blur as a cue; Use of warping in super-resolution; Resolution enhancement using multiple apertures; Super-resolution from motion data; Super-resolution from compressed video; Limits in super-resolution imaging. Written by the leading experts in the field, Super-Resolution Imaging presents a comprehensive analysis of current technology, along with new research findings and directions for future work.
Author: Chu-Song Chen
Publisher: Springer
ISBN: 3319544071
Category : Computers
Languages : en
Pages : 665
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Book Description
The three-volume set, consisting of LNCS 10116, 10117, and 10118, contains carefully reviewed and selected papers presented at 17 workshops held in conjunction with the 13th Asian Conference on Computer Vision, ACCV 2016, in Taipei, Taiwan in November 2016. The 134 full papers presented were selected from 223 submissions. LNCS 10116 contains the papers selected
Author: Ashutosh Aggarwal
Publisher:
ISBN:
Category :
Languages : en
Pages : 166
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Book Description
