NDLI: An unsupervised automatic change detection approach based on visual attention mechanism

Content Provider	IEEE Xplore Digital Library
Author	Donghua Liu Junping Zhang Xiaochen Lu
Copyright Year	2015
Description	Author affiliation: Sch. of Electron. & Inf. Eng., Harbin Inst. of Technol., Harbin, China (Donghua Liu; Junping Zhang; Xiaochen Lu)
Abstract	In change detection analysis, it is important to distinguish the real change targets and pseudo change targets accurately. Supervised change detection has been regarded as the best way to reduce the effects of pseudo change information. This is because human visual system has the ability to find the real changes. By imitating human visual characteristic, visual attention mechanism can bring the improvement of accuracy and speed of unsupervised change detection. In this paper, a change detection approach based on visual attention mechanism is proposed to reduce the influence of pseudo change information. Experiments show that the proposed method significantly reduces the false alarm rate and missed alarm rate and also shows insensitive to noise.
Starting Page	3045
Ending Page	3048
File Size	551848
Page Count	4
File Format	PDF
e-ISBN	9781479979295
DOI	10.1109/IGARSS.2015.7326458
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-26
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Visualization Remote sensing Feature extraction Computational modeling Satellites Visual systems Computer vision saliency map Change detection remote sensing image visual attention feature extraction
Content Type	Text
Resource Type	Article

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