„It has much to offer that is hard to find elsewhere.“ (Journalof the American Statistical Association, December 2006)
„... a well-written book offering comprehensivediscussions... an excellent reference and source book forstatisticians, computer scientists, engineers, and otherresearchers...“ (IIE Transactions- Quality and ReliabilityEngineering, June 2006)
„... an impressive resource for researchstatisticians... researchers in computer graphics and imageprocessing...“ (Technometrics, May 2006)
Image Processing and Jump Regression Analysis
von Peihua QiuThe first text to bridge the gap between image processing andjump regression analysis
Recent statistical tools developed to estimate jump curves andsurfaces have broad applications, specifically in the area of imageprocessing. Often, significant differences in technicalterminologies make communication between the disciplines of imageprocessing and jump regression analysis difficult. Ineasy-to-understand language, Image Processing and JumpRegression Analysis builds a bridge between the worlds ofcomputer graphics and statistics by addressing both the connectionsand the differences between these two disciplines. The authorprovides a systematic analysis of the methodology behindnonparametric jump regression analysis by outlining procedures thatare easy to use, simple to compute, and have proven statisticaltheory 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 localsmoothing
* Edge detection in image processing
* Edge-preserving image restoration
With mathematical proofs kept to a minimum, this book isuniquely accessible to a broad readership. It may be used as aprimary text in nonparametric regression analysis and imageprocessing as well as a reference guide for academicians andindustry professionals focused on image processing or curve/surfaceestimation.
Recent statistical tools developed to estimate jump curves andsurfaces have broad applications, specifically in the area of imageprocessing. Often, significant differences in technicalterminologies make communication between the disciplines of imageprocessing and jump regression analysis difficult. Ineasy-to-understand language, Image Processing and JumpRegression Analysis builds a bridge between the worlds ofcomputer graphics and statistics by addressing both the connectionsand the differences between these two disciplines. The authorprovides a systematic analysis of the methodology behindnonparametric jump regression analysis by outlining procedures thatare easy to use, simple to compute, and have proven statisticaltheory 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 localsmoothing
* Edge detection in image processing
* Edge-preserving image restoration
With mathematical proofs kept to a minimum, this book isuniquely accessible to a broad readership. It may be used as aprimary text in nonparametric regression analysis and imageprocessing as well as a reference guide for academicians andindustry professionals focused on image processing or curve/surfaceestimation.
