Image Processing and Jump Regression Analysis
Wiley Series in Probability and Statistics
1. Auflage Februar 2005
344 Seiten, Hardcover
Wiley & Sons Ltd
Kurzbeschreibung
In recent years, statistical analysis of jump regression models has developed rapidly. One major objective of this book is to introduce these cutting-edge methodologies of jump regression analysis in a systematic way. Thoroughly clarifying connections and differences between jump regression analysis and image processing, this book aims to build a bridge between these two key areas of engineering, to cultivate more effective communication across their respective research groups.
Image Processing and Jump Regression Analysis builds a bridge between the worlds of computer graphics and statistics by addressing both the connections and the differences between these two disciplines. The author provides a systematic breakdown of the methodology behind nonparametric jump regression analysis by outlining procedures that are easy to use, simple to compute, and have proven statistical theory behind them. Key topics include conventional smoothing procedures, estimation of jump regression curves, edge detection in image processing, and edge-preserving image restoration, to name a few. With mathematical proofs kept to a minimum, this book is uniquely accessible as a primary text in nonparametric jump regression analysis and image processing as well as a reference on image processing or curve/surface estimation.
1. Introduction.
2. Basic Statistical Concepts and Conventional Smoothing Techniques.
3. Estimation of Jump Regression Curves.
4. Estimation of Jump Location Curves of Regression Surfaces.
5. Jump Preserving Surface Estimation By Local Smoothing.
6. Edge Detection In Image Processing.
7. Edge-Preserving Image Restoration.
References.
Index.
