Motion-Free Super-Resolution

Motion-Free Super-Resolution
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Artikel-Nr:
9781441938480
Veröffentl:
2010
Einband:
Paperback
Erscheinungsdatum:
29.10.2010
Seiten:
256
Autor:
Joshi Manjunath
Gewicht:
452 g
Format:
235x178x15 mm
Sprache:
Englisch
Beschreibung:

Motion-Free Super-Resolution is a compilation of very recent work on various methods of generating super-resolution (SR) images from a set of low-resolution images. The current literature on this topic deals primarily with the use of motion cues for the purpose of generating SR images. These cues have, it is shown, their advantages and disadvantages. In contrast, this book shows that cues other than motion can also be used for the same purpose, and addresses both the merits and demerits of these new techniques.

Motion-Free Super-Resolution supersedes much of the lead author's previous edited volume, "Super-Resolution Imaging," and includes an up-to-date account of the latest research efforts in this fast-moving field. This sequel also features a style of presentation closer to that of a textbook, with an emphasis on teaching and explanation rather than scholarly presentation.

With the explosion of Internet technology and graphics engines, digital images are now everywhere. Image capturing tools are all pervading - in our pockets to inside a satellite. And although imaging applications demand an availability to high resolution images, such images are not picture perfect and may be lacking sufficient details. This requires that these images be super-resolved for improved details. How to achieve this is what constitutes research in the area of image super-resolution.
Motion-Free Super-Resolution explores new technology for image super-resolution - applying cues other than the motion cue in super-resolving a scene. This book will serve as an essential reference for both academecians and practicing engineers in the area of image processing and computer vision, as well as providing a basis for ongoing research in this field.
Research on Image Super-Resolution.- Use of Defocus Cue.- Photometry Based Method.- Blind Restoration of Photometric Observations.- Use of Learnt Wavelet Coefficients.- Extension of Generalized Interpolation to Eigen Decomposition.- Use of Zoom Cue.- Looking Ahead.

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