Image Processing and Jump Regression Analysis

Передня обкладинка
John Wiley & Sons, 20 трав. 2005 р. - 344 стор.
The first text to bridge the gap between image processing and jump regression analysis

Recent statistical tools developed to estimate jump curves and surfaces have broad applications, specifically in the area of image processing. Often, significant differences in technical terminologies make communication between the disciplines of image processing and jump regression analysis difficult. In easy-to-understand language, 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 analysis 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
  • Estimation of jump location curves of regression surfaces
  • Jump-preserving surface reconstruction based on local smoothing
  • Edge detection in image processing
  • Edge-preserving image restoration

With mathematical proofs kept to a minimum, this book is uniquely accessible to a broad readership. It may be used as a primary text in nonparametric regression analysis and image processing as well as a reference guide for academicians and industry professionals focused on image processing or curve/surface estimation.

 

Вибрані сторінки

Зміст

1 Introduction
1
2 Basic Statistical Concepts and Conventional Smoothing Techniques
13
3 Estimation of Jump Regression Curves
55
4 Estimation of Jump Location Curves of Regression Surfaces
101
5 JumpPreserving Surface Estimation By Local Smoothing
149
6 Edge Detection In Image Processing
187
7 EdgePreserving Image Restoration
233
References
281
Index
301
Авторські права

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Image Processing and Jump Regression Analysis
Peihua Qiu
Попередній перегляд недоступний - 2005
Image Processing and Jump Regression Analysis
Peihua Qiu
Попередній перегляд недоступний - 2005

Загальні терміни та фрази

algorithm applications bandwidth basis functions coefficients computation curve defined defined in equation definition denotes design interval design points design space detected edges detectors discrete wavelet transformations discussed in Subsection edge detection edge pixels edge segment estimate f estimator of f expression first first-order derivative fitted Fourier transformation function f Geman given point gray levels Hausdorff distance image gradient image intensity function image processing image restoration jump candidates jump detection criterion jump detection procedure jump magnitudes jump positions jump regression kernel function linear kernel estimator literature mask neighborhood noise nonparametric regression number of jumps parameter plot pointset polynomial possible jump problem procedures discussed random variable regression analysis regression function regression model regression surface restored image sample satisfies shown in Figure smoothing procedures specific spline spline estimator Statistical step edge surface estimator surface reconstruction threshold value true image true JLC weighted

Про автора (2005)

PEIHUA QIU, PHD, is Associate Professor of Statistics at the University of Minnesota. He has published over twenty-five papers in refereed journals as well as two book chapters. He received his PhD in Statistics at the University of Wisconsin-Madison in 1996.

Бібліографічна інформація

НазваImage Processing and Jump Regression Analysis
Wiley Series in Probability and Statistics
АвторPeihua Qiu
Виданняілюстроване
ВидавецьJohn Wiley & Sons, 2005
ISBN0471733164, 9780471733164
Обсяг344 стор.
  
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