AN INVESTIGATION ON SOME SEQUENTIAL ALGORITHMS FOR TERRAIN CLASSIFICATION

被引：0

作者：

HUANG, Y ^{[1
]}

ZAMPERONI, P ^{[1
]}

机构：

[1] TECH UNIV CAROLO WILHELMINA BRAUNSCHWEIG,INST NACHRICHTENTECH,SCHLEINITZSTR 23,W-3300 BRAUNSCHWEIG,GERMANY

来源：

PATTERN RECOGNITION LETTERS | 1993年 / 14卷 / 06期

关键词：

SEQUENTIAL PROBABILITY RATIO TEST; MULTICLASS CLASSIFICATION; REMOTE SENSING IMAGES;

D O I：

10.1016/0167-8655(93)90033-A

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes three extensions of the sequential probability ratio test (SPRT) algorithm (Fu (1968)), originally developed as a two-class classifier, to the multi-class classification problem. These sequential methods have been applied to the crop classification in remote sensing images taken from agricultural areas. The performances of the considered methods are compared and the classification scores are given.

引用

页码：523 / 529

页数：7

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