Example-Based Super Resolution
Author:   Jordi Salvador (Senior Scientist, Technicolor R&I, Hannover, Germany)
Publisher:   Elsevier Science Publishing Co Inc
ISBN:  

9780128097038


Pages:   162
Publication Date:   23 September 2016
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Example-Based Super Resolution


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Author:   Jordi Salvador (Senior Scientist, Technicolor R&I, Hannover, Germany)
Publisher:   Elsevier Science Publishing Co Inc
Imprint:   Academic Press Inc
Dimensions:   Width: 15.20cm , Height: 1.00cm , Length: 22.90cm
Weight:   0.190kg
ISBN:  

9780128097038


ISBN 10:   0128097035
Pages:   162
Publication Date:   23 September 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1: Classic Multiframe Super Resolution Chapter 2: A Taxonomy of Example-Based Super Resolution Chapter 3: High-Frequency Transfer Chapter 4: Neighbor Embedding Chapter 5: Sparse Coding Chapter 6: Anchored Regression Chapter 7: Trees and Forests Chapter 8: Deep Learning Chapter 9: Conclusions

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Author Information

Jordi Salvador holds a senior scientist position at Technicolor R&I in Hannover and is member of Technicolor’s Fellowship Network. His main focus is the research of new algorithms for example-based super resolution and machine learning. Formerly, he received a M.Sc. in Telecommunications (equivalent to Electrical) Engineering in 2006 and a M.Sc. in the European MERIT program in 2008, both from the Universitat Polit`ecnica de Catalunya (UPC) in Barcelona. He obtained the Ph.D. degree in 2011, also from UPC, where he contributed to projects of the Spanish Science and Technology System (VISION,PROVEC) and also to a European FP6 project (CHIL) as research assistant on multiview reconstruction. His research interests include 3D reconstruction, real-time and parallel algorithms, new computer-human interfaces, image and video restoration, super resolution, inverse problems and machine learning.

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