Inverse Problems in Vision and 3D Tomography

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 15–58): Ali Mohammad?DjafariChapter 2 Noise Removal and Contour Detection (pages 59–95): Pierre Charbonnier and Christophe ColletChapter 3 Blind Image Deconvolution (pages 97–121): Laure Blanc?Feraud, Laurent Mugnier and Andre JalobeanuChapter 4 Triplet Markov Chains and Image Segmentation (pages 123–153): Wojciech PieczynskiChapter 5 Detection and Recognition of a Collection of Objects in a Scene (pages 155–189): Xavier Descombes, Ian Jermyn and Josiane ZerubiaChapter 6 Apparent Motion Estimation and Visual Tracking (pages 191–249): Etienne Memin and Patrick PerezChapter 7 Super?Resolution (pages 251–275): Ali Mohammad?Djafari and Fabrice HumblotChapter 8 Surface Reconstruction from Tomography Data (pages 277–308): Charles Soussen and Ali Mohammad?DjafariChapter 9 Gauss?Markov?Potts Prior for Bayesian Inversion in Microwave Imaging (pages 309–338): Olivier Feron, Bernard Duchene and Ali Mohammad?DjafariChapter 10 Shape from Shading (pages 339–376): Jean?Denis DurouChapter 11 Image Separation (pages 377–410): Hichem Snoussi and Ali Mohammad?DjafariChapter 12 Stereo Reconstruction in Satellite and Aerial Imaging (pages 411–436): Julie Delon and Andres AlmansaChapter 13 Fusion and Multi?Modality (pages 437–460): Christophe Collet, Farid Flitti, Stephanie Bricq and Andre Jalobeanu