The importance of mathematics in the study of problems arising from the real world, and the increasing success with which it has been used to model situations ranging from the purely deterministic to the stochastic, in all areas of today's Physical Sciences and Engineering, is well established. The
Inverse Problems in Vision and 3D Tomography
- Publisher
- Wiley-ISTE
- Year
- 2009
- Tongue
- English
- Leaves
- 460
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
The concept of an inverse problem is a familiar one to most scientists and engineers, particularly in the field of signal and image processing, imaging systems (medical, geophysical, industrial non-destructive testing, etc.) and computer vision. In imaging systems, the aim is not just to estimate unobserved images, but also their geometric characteristics from observed quantities that are linked to these unobserved quantities through the forward problem. This book focuses on imagery and vision problems that can be clearly written in terms of an inverse problem where an estimate for the image and its geometrical attributes (contours and regions) is sought.
The chapters of this book use a consistent methodology to examine inverse problems such as: noise removal; restoration by deconvolution; 2D or 3D reconstruction in X-ray, tomography or microwave imaging; reconstruction of the surface of a 3D object using X-ray tomography or making use of its shading; reconstruction of the surface of a 3D landscape based on several satellite photos; super-resolution; motion estimation in a sequence of images; separation of several images mixed using instruments with different sensitivities or transfer functions; and more.Content:
Chapter 1 Introduction to Inverse Problems in Imaging and Vision (pages 15โ58): Ali Mohammad?Djafari
Chapter 2 Noise Removal and Contour Detection (pages 59โ95): Pierre Charbonnier and Christophe Collet
Chapter 3 Blind Image Deconvolution (pages 97โ121): Laure Blanc?Feraud, Laurent Mugnier and Andre Jalobeanu
Chapter 4 Triplet Markov Chains and Image Segmentation (pages 123โ153): Wojciech Pieczynski
Chapter 5 Detection and Recognition of a Collection of Objects in a Scene (pages 155โ189): Xavier Descombes, Ian Jermyn and Josiane Zerubia
Chapter 6 Apparent Motion Estimation and Visual Tracking (pages 191โ249): Etienne Memin and Patrick Perez
Chapter 7 Super?Resolution (pages 251โ275): Ali Mohammad?Djafari and Fabrice Humblot
Chapter 8 Surface Reconstruction from Tomography Data (pages 277โ308): Charles Soussen and Ali Mohammad?Djafari
Chapter 9 Gauss?Markov?Potts Prior for Bayesian Inversion in Microwave Imaging (pages 309โ338): Olivier Feron, Bernard Duchene and Ali Mohammad?Djafari
Chapter 10 Shape from Shading (pages 339โ376): Jean?Denis Durou
Chapter 11 Image Separation (pages 377โ410): Hichem Snoussi and Ali Mohammad?Djafari
Chapter 12 Stereo Reconstruction in Satellite and Aerial Imaging (pages 411โ436): Julie Delon and Andres Almansa
Chapter 13 Fusion and Multi?Modality (pages 437โ460): Christophe Collet, Farid Flitti, Stephanie Bricq and Andre Jalobeanu
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