Example-based Super Resolution
Jordi Salvador
Elsevier Academic Press, 2016
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About
The book 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.
Topics covered by the book
- Classic multiframe Super Resolution
- Example-based Super-Resolution taxonomy
- High-frequency transfer
- Neighbor embedding
- Sparse coding
- Anchored regression
- Trees and forests
- Deep learning
BibTeX
@book{Salvador2016,author = {Salvador, J.},
title = {{Example-based Super Resolution}},
publisher = {{Elsevier Academic Press}},
year = {2016},
edition = {1},
isbn = {9780128097038},
}
