Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization 1st ed. 2016 Edition

  • By Mongi A. Abidi, Andrei V. Gribok, Joonki Paik
  • Pages 293
  • Year 2016
  • Publisher Springer
  • Language en
  • ISBN 9783319463636
  • File Size 5.52 MB
  • File Format PDF
  • Download Counter 451
  • Amazon Link

Ebook Description

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 the best solution based on numerical minimization of a single, scalar-valued objective function or cost function. Unconstrained optimization problems have been intensively studied, and many algorithms and tools have been developed to solve them.


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