Items related to Optimization Techniques in Computer Vision: Ill-Posed...
Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization (Advances in Computer Vision and Pattern Recognition) - Hardcover
Synopsis
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. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems. The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc.
Optimization plays a major role in a wide variety of theories for image processing and computer vision. Various optimization techniques are used at different levels for these problems, and this volume summarizes and explains these techniques as applied to image processing and computer vision.
"synopsis" may belong to another edition of this title.
Review
“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)
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2016
- ISBN 10 3319463632
- ISBN 13 9783319463636
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages308
Buy New
View this item
US$ 161.77
US$ 15.89 shipping from United Kingdom to U.S.A.
Destination, rates & speeds
Search results for Optimization Techniques in Computer Vision: Ill-Posed...
Stock Image
Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization (Advances in Computer Vision and Pattern Recognition)
Published by
Springer (edition 1st ed. 2016), 2016
ISBN 10: 3319463632
ISBN 13: 9783319463636
Used
Hardcover
Seller: BooksRun, Philadelphia, PA, U.S.A.
Seller rating 5 out of 5 stars
Hardcover. Condition: Good. 1st ed. 2016. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported. Seller Inventory # 3319463632-11-1
Quantity: 1 available
Stock Image
Optimization Techniques in Computer Vision. Ill-Posed Problems and Regularization.
Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
Seller rating 4 out of 5 stars
xv, 293 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Seller Inventory # 11709DB
Quantity: 1 available
Stock Image
Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization (Advances in Computer Vision and Pattern Recognition)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In. Seller Inventory # ria9783319463636_new
Quantity: Over 20 available
Seller Image
Optimization Techniques in Computer Vision
Published by
Springer International Publishing Dez 2016, 2016
ISBN 10: 3319463632
ISBN 13: 9783319463636
New
Hardcover
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems. The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc.Optimization plays a major role in a wide variety of theories for image processing and computer vision.Various optimization techniques are used at different levels for these problems, and this volume summarizes and explains these techniques as applied to image processing and computer vision. 312 pp. Englisch. Seller Inventory # 9783319463636
Quantity: 2 available
Seller Image
Optimization Techniques in Computer Vision
Published by
Springer International Publishing, 2016
ISBN 10: 3319463632
ISBN 13: 9783319463636
New
Hardcover
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Features a comprehensive description of regularization through optimizationContains a large selection of data fusion algorithmsIncludes chapters devoted to video compression and enhancementThis book pr. Seller Inventory # 128452365
Quantity: Over 20 available
Seller Image
Optimization Techniques in Computer Vision : Ill-Posed Problems and Regularization
Published by
Springer International Publishing, 2016
ISBN 10: 3319463632
ISBN 13: 9783319463636
New
Hardcover
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Most practical optimization problems, however, arise with a set of constraints. Typical examples of constraints include: (i) pre-specified pixel intensity range, (ii) smoothness or correlation with neighboring information, (iii) existence on a certain contour of lines or curves, and (iv) given statistical or spectral characteristics of the solution. Regularized optimization is a special method used to solve a class of constrained optimization problems.The term regularization refers to the transformation of an objective function with constraints into a different objective function, automatically reflecting constraints in the unconstrained minimization process. Because of its simplicity and efficiency, regularized optimization has many application areas, such as image restoration, image reconstruction, optical flow estimation, etc.Optimization plays a major role in a wide variety of theories for image processing and computer vision.Various optimization techniques are used at different levels for these problems, and this volume summarizes and explains these techniques as applied to image processing and computer vision. Seller Inventory # 9783319463636
Quantity: 1 available
Stock Image
Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization (Advances in Computer Vision and Pattern Recognition)
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. Seller Inventory # 26375007629
Quantity: 4 available
Stock Image
Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization
Seller: Revaluation Books, Exeter, United Kingdom
Seller rating 5 out of 5 stars
Hardcover. Condition: Brand New. 312 pages. 9.50x6.50x1.00 inches. In Stock. Seller Inventory # x-3319463632
Quantity: 2 available
Stock Image
Optimization Techniques in Computer Vision: Ill-Posed Problems and Regularization (Advances in Computer Vision and Pattern Recognition)
Seller: Mispah books, Redhill, SURRE, United Kingdom
Seller rating 4 out of 5 stars
Hardcover. Condition: Like New. Like New. book. Seller Inventory # ERICA77333194636326
Quantity: 1 available