3-D Shape Estimation and Image Restoration

Stefano Soatto

ISBN 10: 1849965595 / ISBN 13: 9781849965590

Verlag: Springer London, Springer London Feb 2013, 2013

Beschreibung

Neuware -Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer thr- dimensional information. For instance, if the scene contains objects made with homogeneous material, such as marble, variations in image intensity can be - sociated with variations in shape, and hence the ¿shading¿ in the image can be exploited to infer the ¿shape¿ of the scene (shape from shading). Similarly, if the scene contains (statistically) regular structures, variations in image intensity can be used to infer shape (shape from textures). Shading, texture, cast shadows, - cluding boundaries are all ¿cues¿ that can be exploited to infer spatial properties of the scene from a single image, when the underlying assumptions are sat- ed. In addition, one can obtain spatial cues from multiple images of the same scene taken with changing conditions. For instance, changes in the image due to a moving light source are used in ¿photometric stereo,¿ changes in the image due to changes in the position of the cameras are used in ¿stereo,¿ ¿structure from motion,¿ and ¿motion blur. ¿ Finally, changes in the image due to changes in the geometry of the camera are used in ¿shape from defocus. ¿ In this book, we will concentrate on the latter two approaches, motion blur and defocus, which are referred to collectively as ¿accommodation cues.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 264 pp. Englisch.

Bestandsnummer des Verkäufers 9781849965590

Bibliografische Details

• Titel: 3-D Shape Estimation and Image Restoration
• Verlag: Springer London, Springer London Feb 2013
• Erscheinungsjahr: 2013
• Sprache: Englisch
• ISBN-10: 1849965595
• ISBN-13: 9781849965590
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer three-dimensional information. This useful volume concentrates on motion blur and defocus, which can be exploited to infer the 3-D structure of a scene — as well as its radiance properties — and which in turn can be used to generate novel images with better quality. The book presents a coherent analytical framework for the analysis and design of algorithms to estimate 3-D shape from defocused and motion blurred images, and to eliminate defocus and motion blur to yield "restored" images. It further provides a collection of algorithms that are optimal with respect to the chosen model and estimation criterion.

Von der hinteren Coverseite

Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer three-dimensional information. This useful volume concentrates on motion blur and defocus, which can be exploited to infer the 3-D structure of a scene as well as its radiance properties and which in turn can be used to generate novel images with better quality.

3-D Shape Estimation and Image Restoration presents a coherent framework for the analysis and design of algorithms to estimate 3-D shape from defocused and motion blurred images, and to eliminate defocus and motion blur to yield "restored" images. It provides a collection of algorithms that are optimal with respect to the chosen model and estimation criterion.

Topics and Features include:

Comprehensive introduction to guide readers through the different areas of the topic

Basic models of image formation

Discussion of least-squares shape from defocus

Unifying defocus and motion blur

Handling multiple moving objects

Dealing with occlusions

Appendices supply the necessary background in optimization and regularization

www.eps.hw.ac.uk/~pf21/FavaroSoattoBook/downloads contains implementations of relevant algorithms, test data and demos.

Written for readers with interests in image processing and computer vision and with backgrounds in engineering, science or mathematics, this highly practical text/reference is accessible to advanced students or those with a degree that includes basic linear algebra and calculus courses. It can also be seen as a resource for practitioners looking to expand their knowledge in the subject.