Optimization Techniques in Computer Vision Ill-Posed Problems and Regularization /

• Κύριοι συγγραφείς: Abidi, Mongi A. (Συγγραφέας), Gribok, Andrei V. (Συγγραφέας), Paik, Joonki (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Σειρά: Advances in Computer Vision and Pattern Recognition,
• Θέματα: Computer science.; Algorithms.; Image processing.; Computer science > Mathematics.; Computer mathematics.; Computer Science.; Image Processing and Computer Vision.; Signal, Image and Speech Processing.; Algorithm Analysis and Problem Complexity.; Mathematical Applications in Computer Science.

This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems. Unconstrained optimization gives th...

Πίνακας περιεχομένων:

• 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.