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information. In contrast with other methods, our method shows good performance in
the detection of fine edge part and has less isolate pixels. It should be pointed out that
the result obtained by the proposed method is very close to the reference map, from
the visual analysis of Figs. 4 and 5.
Fig. 4. Change detection results of different methods on the Mexico dataset. (a) NTC, (b) DTC,
(c) UDWT, (d) our method.
Fig. 5. Change detection results of different methods on the Sardinia dataset. (a) NTC, (b)
DTC, (c) UDWT, (d) our method.
Tables 1 and 2 show the quantitative results for the two datasets respectively. As
can be seen, our method has the least number of false alarms and the most number of
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