Image chain assessment for feature extraction

被引：2

作者：

Cofer, RH ^{[1
]}

Kozaitis, SP ^{[1
]}

机构：

[1] Florida Inst Technol, Dept Elect & Comp Engn, Melbourne, FL 32901 USA

来源：

VISUAL INFORMATION PROCESSING XII | 2003年 / 5108卷

关键词：

feature extraction; Bayesian detector; image chain;

D O I：

10.1117/12.487029

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

It is shown that the image chain has important effects upon the quality of feature extraction. Exact analytic ROC results are given for the case where arbitrary multivariate normal imagery is passed to a Bayesian feature detector designed for multivariate normal imagery with a diagonal covariance matrix. Plots are provided to allow direct visual inspection of many of the more readily apparent effects. Also shown is an analytic tradeoff that says doubling background contrast is equal to halving sensor to scene distance or sensor noise. It is also shown that the results provide a lower bound to the ROC of a Bayesian feature detector designed for arbitrary multivariate normal distributions.

引用

页码：287 / 294

页数：8