RT Journal Article
T1 Performance of Change Detection Algorithms Using Heterogeneous Images and Extended Multi-attribute Profiles (EMAPs)
A1 Kwan, Chiman
A1 Ayhan, Bulent
A1 Larkin, Jude
A1 Kwan, Liyun
A1 Bernabé García, Sergio
A1 Plaza, Antonio
AB We present detection performance of ten change detection algorithms with and without the use of Extended Multi-Attribute Profiles (EMAPs). Heterogeneous image pairs (also known as multimodal image pairs), which are acquired by different imagers, are used as the pre-event and post-event images in the investigations. The objective of this work is to examine if the use of EMAP, which generates synthetic bands, can improve the detection performances of these change detection algorithms. Extensive experiments using five heterogeneous image pairs and ten change detection algorithms were carried out. It was observed that in 34 out of 50 cases, change detection performance was improved with EMAP. A consistent detection performance boost in all five datasets was observed with EMAP for Homogeneous Pixel Transformation (HPT), Chronochrome (CC), and Covariance Equalization (CE) change detection algorithms.
PB MDPI
SN 2072-4292
YR 2019
FD 2019-10-14
LK https://hdl.handle.net/20.500.14352/12684
UL https://hdl.handle.net/20.500.14352/12684
LA eng
NO Defense Advanced Research Projects Agency (DARPA)
DS Docta Complutense
RD 7 abr 2025