- Full Description
This book presents a coherent framework for the analysis & design of algorithms to estimate 3-D shape from defocused & motion blurred images, & to eliminate defocus & motion blur to yield 'restored' images. It provides a collection of algorithms that are optimal with respect to the chosen model & estimation criterion. Topics & Features: • Comprehensive introduction • Basic models of image formation • Discussion of least-squares shape from defocus • Unifying defocus & motion blur • Handling multiple moving objects • Dealing with occlusions • Appendices supply the necessary background in optimization & regularization • www.eps.hw.ac.uk/~pf21/FavaroSoattoBook/downloads contains implementations of relevant algorithms, test data & demos. Written for readers with interests in image processing & computer vision & 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 & calculus courses.
- Table of Contents
Table of Contents
- Visual Cues for Shape and Motion.
- Basic Models of Image Formation.
- When Can 3D Shape Be Reconstructed from Blurred Images?
- A First Solution: Least
- Enforcing Positivity.
- Defocus via Diffusion: Modeling and Reconstruction from Two Views.
- Shape from the Defocus of Multiple Images.
- Modeling Motion
- Blur and Defocus via Diffusion.
- Dealing with Occlusions.
- Conclusions and Open Issues.
- Appendixes: Concepts of Radiometry.
- A PDE Primer.
- Proofs of Propositions.
- Calibration of Defocused Images.
- Matlab® Implementation of Some Algorithms.
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