3-D Shape Estimation and Image Restoration

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3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur , Stefano Soatto
Springer | 2006 | English | ISBN 1846281768 | 249 pages | PDF | 9 Mb

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


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