Titlebook: Image Mosaicing and Super-resolution; David Capel Book 2004 Springer-Verlag London 2004 Image mosicing.Image registration.Super-resolution

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Introduction, beyond that of any 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.

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Book 2004produce 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

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Introduction,o produce single images of superior quality. The generic name for such techniques is .. Using frame fusion, it is possible to extend the field of view beyond that of any single image, to reduce noise, to restore high-frequency content, and even to increase spatial resolution and dynamic range. The a

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Image Mosaicing,n this chapter are concerned with images which can be registered by means of a planar homography: views of a planar scene from arbitrary viewpoints, or views of a scene taken by a rotating camera. There are three important factors to consider when constructing a mosaic: the estimation of a set of ho

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Super-resolution Using Bayesian Priors,ihood estimator of the super-resolution image is a highly ill-conditioned inverse problem. Consequently, the solution is extremely sensitive to noise in the observed images and to errors in registration. It is notable that, in cases where the ML estimator performs poorly, the resulting super-resolut

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ong anti-interference capability of satellite signal, has become an important development trend of satellite navigation enhancement. In view of the problems such as weak landing signals of BeiDou-3 Navigation Satellite System (BDS-3) and vulnerability to external spoofing, combined with the potentia

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