Optimization Techniques in Computer Vision

Ill-Posed Problems and Regularization

Häftad, Engelska, 2018

AvMongi A. Abidi,Andrei V. Gribok,Joonki Paik

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This book presents practical optimization techniques used in image processing and computer vision problems.

Produktinformation

Utgivningsdatum2018-07-04
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieAdvances in Computer Vision and Pattern Recognition
Antal sidor293
FörlagSpringer International Publishing AG
ISBN9783319835013

Tillhör följande kategorier

Ill-Posed Problems in Imaging and Computer Vision.- Selection of the Regularization Parameter.- Introduction to Optimization.- Unconstrained Optimization.- Constrained Optimization.- Frequency-Domain Implementation of Regularization.- Iterative Methods.- Regularized Image Interpolation Based on Data Fusion.- Enhancement of Compressed Video.- Volumetric Description of Three-Dimensional Objects for Object Recognition.- Regularized 3D Image Smoothing.- Multi-Modal Scene Reconstruction Using Genetic Algorithm-Based Optimization.- Appendix A: Matrix-Vector Representation for Signal Transformation.- Appendix B: Discrete Fourier Transform.- Appendix C: 3D Data Acquisition and Geometric Surface Reconstruction.- Appendix D: Mathematical Appendix.- Index.

“The presentation of the problems is accompanied by illustrating examples. The book contains both a great theoretical background and practical applications and is thus self-contained. It is useful for master and doctoral students, as well as for researchers and practitioners dealing with computer vision and image processing, but also working in mathematical optimization.” (Ruxandra Stoean, zbMATH 1362.68003, 2017)