Example-Based Super Resolution
Auteur : Salvador Jordi
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
Computer vision scientists and researchers with undergraduate-level statistics knowledge whose work is related to imaging. Machine learning, image processing, and research and development communities.
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.
- Provides detailed coverage of techniques and implementation details that have been successfully introduced in diverse and demanding real-world applications
- Covers a wide variety of machine learning approaches, ranging from cross-scale self-similarity concepts and sparse coding, to the latest advances in deep learning
- Presents a statistical interpretation of the subspace of natural image patches that transcends super resolution and makes it a valuable source for any researcher on image processing or low-level vision
Date de parution : 09-2016
Ouvrage de 162 p.
15x22.8 cm
Thème d’Example-Based Super Resolution :
Mots-clés :
Super resolution; Image processing; Deblurring; Denoising; Statistical models; Sparse coding; Deep learning