3-D Shape Estimation and Image Restoration

Exploiting Defocus and Motion-Blur
1. Auflage. 2006
ISBN: 978-1-84628-176-1
Verlag: Springer

Buch, Englisch, 249 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 565 g

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.

Zielgruppe

Graduate students in Programming; researchers in Computer Vision and Image Processing

Autoren/Hrsg.

Favaro, Paolo

Soatto, Stefano

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung

Inhaltsverzeichnis

Basic models of image formation.- Some analysis: When can 3-D shape be reconstructed from blurred images?.- Least-squares shape from defocus.- Enforcing positivity: Shape from defocus and image restoration by minimizing I-divergence.- Defocus via diffusion: Modeling and reconstruction.- Dealing with motion: Unifying defocus and motion blur.- Dealing with multiple moving objects.- Dealing with occlusions.- Final remarks.