Iterative-Interpolation Super-Resolution Image Reconstruction : A Computationally Efficient Technique

Vivek Bannore

ISBN 10: 3642003842 / ISBN 13: 9783642003844

Published by Springer, Berlin, Springer Berlin Heidelberg, Springer, 2009

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783642003844

Bibliographic Details

• Title: Iterative-Interpolation Super-Resolution Image Reconstruction : A Computationally Efficient Technique
• Publisher: Springer, Berlin, Springer Berlin Heidelberg, Springer
• Publication Date: 2009
• Language: English
• ISBN 10: 3642003842
• ISBN 13: 9783642003844
• Binding: Buch
• Condition: Neu

About this title

Synopsis

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.

From the Back Cover

This book presents a novel and hybrid, computationally efficient, reconstruction scheme for solving the problem of super-resolution restoration of high-resolution images from sequences of geometrically warped, aliased and under-sampled low-resolution images. The scheme proposed is referred as the Iterative-Interpolation Super-Resolution (IISR) technique. The optimization-based technique for super-resolution is reinvestigated for comparative analysis to evaluate the accuracy and efficiency of the IISR technique. The significant influence of the regularization term over the fidelity of reconstruction is also analysed. The IISR technique addresses the problem of super-resolution image enhancement in terms of maintaining highest fidelity of reconstruction and a low computational cost to achieve maximum applicability of super-resolution to the real-world applications.