Natural Image Statistics— A probabilistic approach to early computational visionAapo Hyvärinen, Jarmo Hurri, and Patrik O. HoyerBook published by Springer-Verlag, 2009. Order from: Springer Amazon.co.uk Amazon.comDownloads: Full preprint version in pdf, 487 pages, 9 MB (Feb 2009 version) Matlab code and image data for reproducing most experiments, 1.5 MB Errata (Aug 2014) |
From the preface:
This book is both an introductory textbook and a research monograph on modelling the statistical structure of natural images. In very simple terms, ``natural images'' are photographs of the typical environment where we live. In this book, their statistical structure is described using a number of statistical models whose parameters are estimated from image samples.
Our main motivation for exploring natural image statistics is computational modelling of biological visual systems. A theoretical framework which is gaining more and more support considers the properties of the visual system to be reflections of the statistical structure of natural images, because of evolutionary adaptation processes. Another motivation for natural image statistics research is in computer science and engineering, where it helps in development of better image processing and computer vision methods.
The book is targeted for advanced undergraduate students, graduate students and researchers in vision science, computational neuroscience, computer vision and image processing. It can also be read as an introduction to the area by people with a background in mathematical disciplines (mathematics, statistics, theoretical physics). Due to the multidisciplinary nature of the subject, the book has been written so as to be accessible to an audience coming from very different backgrounds such as psychology, computer science, electrical engineering, neurobiology, mathematics, statistics and physics.
Updated by Aapo Hyvärinen, Jan 2015