Iterative-Interpolation Super-Resolution Image Reconstruction
A Computationally Efficient Technique
Seiten
2010
|
1. Softcover reprint of hardcover 1st ed. 2009
Springer Berlin (Verlag)
978-3-642-10145-8 (ISBN)
Springer Berlin (Verlag)
978-3-642-10145-8 (ISBN)
This book presents a novel, 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.
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.
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.
to Super-Resolution.- Overview of Super-Resolution Techniques.- Iterative-Interpolation Super-Resolution (IISR).- Optimization Approach to Super-Resolution Image Reconstruction.- Image Registration for Super-Resolution.- Software Framework.- Conclusion and Future Directions.
| Erscheint lt. Verlag | 28.10.2010 |
|---|---|
| Reihe/Serie | Studies in Computational Intelligence |
| Zusatzinfo | XIII, 113 p. |
| Verlagsort | Berlin |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 203 g |
| Themenwelt | Geisteswissenschaften ► Psychologie ► Biopsychologie / Neurowissenschaften |
| Informatik ► Grafik / Design ► Digitale Bildverarbeitung | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
| Technik | |
| Schlagworte | Bildbearbeitung • Computational Intelligence • Image Processing • Image Registration • Intelligent Image Super-resolution Techniques • Interpolation • Optimization • pattern recognition |
| ISBN-10 | 3-642-10145-3 / 3642101453 |
| ISBN-13 | 978-3-642-10145-8 / 9783642101458 |
| Zustand | Neuware |
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