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

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Abidi, Mongi A. (Autor), Gribok, Andrei V. (Autor), Paik, Joonki (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Advances in Computer Vision and Pattern Recognition,
Temas:
Computer vision.
Signal processing.
Algorithms.
Computer science-Mathematics.
Computer Vision.
Signal, Speech and Image Processing .
Mathematical Applications in Computer Science.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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