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Example-Based Super Resolution

This thorough introduction of example-based super resolution covers the most successful algorithmic approaches and theories with implementation insights

Jordi Salvador (Author)

9780128097038, Elsevier Science

Paperback, published 23 September 2016

162 pages
22.9 x 15.1 x 1.2 cm, 0.19 kg

Example-Based Super Resolution provides a thorough introduction and overview of example-based super resolution, covering the most successful algorithmic approaches and theories behind them with implementation insights. It also describes current challenges and explores future trends.

Readers of this book will be able to understand the latest natural image patch statistical models and the performance limits of example-based super resolution algorithms, select the best state-of-the-art algorithmic alternative and tune it for specific use cases, and quickly put into practice implementations of the latest and most successful example-based super-resolution methods.

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

Subject Areas: Image processing [UYT]

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