A COMPARISON OF SELF-DUAL ATTRIBUTE PROFILES BASED ON DIFFERENT FILTER RULES FOR CLASSIFICATION

被引：11

作者：

Cavallaro, Gabriele ^{[1
]}

Mura, Mauro Dalla

Benediktsson, Jon Atli ^{[1
]}

Bruzzone, Lorenzo

机构：

[1] Univ Iceland, Fac Elect & Comp Engn, Reykjavik, Iceland

来源：

2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年

关键词：

image processing; mathematical morphology; connected filters; tree representations; CONNECTED OPERATORS; IMAGE;

D O I：

10.1109/IGARSS.2014.6946663

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper we compare features obtained by different filtering strategies for morphological attribute filters by considering non-increasing attributes. The Attribute profiles (APs) and Self Dual Attribute Profiles (SDAPs) are obtained by sequentially applying attribute filters on tree-based image representations, such as Min- or Max-trees and Inclusion tree, respectively. This work aims to study the effects of using the filtering rules max, min, direct and subtractive, when considering the non-increasing attributes moment of inertia and standard deviation. A very high spatial resolution data set is used in the experiments, and the extracted information obtained by the profiles is analyzed. This is done by studying the effects on the classification accuracy by using the profiles as additional input features to a Random Forest classifier

引用

页码：1265 / 1268

页数：4

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