Book123

    Free register and download UseNet downloader, then you can FREE Download from UseNet.

    Download without Limit " Study Natural Image Statistics: A Probablistic Approach to Early Computational Vision with Matlab code " from UseNet for FREE!

More

Aapo Hyvärinen, Jarmo Hurri, Patrick O. Hoyer, “Natural Image Statistics: A Probablistic Approach to Early Computational Vision with Matlab code”

One of the most successful frameworks in computational neuroscience is modelling visual processing using the statistical structure of natural images. In this framework, the visual system of the brain constructs a model of the statistical regularities of the incoming visual data. This enables the visual system to perform efficient probabilistic inference. The same framework is also very useful in engineering applications such as image processing and computer vision.

This book is the first comprehensive introduction to the multidisciplinary field of natural image statistics. The book starts with a review of background material in signal processing and neuroscience, which makes it accessible to a wide audience. The book then explains both the basic theory and the most recent advances in a coherent and user-friendly manner. This structure, together with the included exercises and computer assignments, also make it an excellent textbook.

Natural Image Statistics is a timely and valuable resource for advanced students and researchers in any discipline related to vision, such as neuroscience, computer science, psychology, electrical engineering, cognitive science or statistics.

Table of contents

1. Introduction.- Part I Background.- 2. Linear Filters and Frequency Analysis.- 3. Outline of the Visual System.- 4. Multivariate Probability and Statistics.- Part II Statistics of Linear Features.- 5. Principal Components and Whitening.- 6. Sparse Coding and Simple Cells.- 7. Independent Component Analysis.- 8. Information-Theoretic Interpretations.- Part III Nonlinear Features and Dependency of Linear Features.- 9. Energy Correlation of Linear Features and Normalisation.- 10. Energy Detectors and Complex Cells.- 11. Energy Correlations and Topographic Organisation.- 12. Dependencies of Energy Detectors; Beyond V1.- 13. Overcomplete and Non-Negative Models.- 14. Lateral Interactions and Feedback.- Part IV Time, Colour and Stereo.- 15. Colour and Stereo Images.- 16. Temporal Sequences of Natural Images.- Part V Conclusion.- 17. Conclusion and Future Prospects.- Part VI Appendix: Supplementary Mathematical Tools.- 18. Optimisation Theory and Algorithms.- 19. Crash Course on Linear Algebra.- 20. The Discrete Fourier Transform.- 21. Estimation of Non-Normalised Statistical Models.- Index.- References.

Buy Book at Lowest Price on Amazon

Only RS mirrors, please

thanks.

RS mirror:

Rating:
2.5 out of 5 by Book123