Unsupervised change detection in satellite images using oversegmentation and mutual information

Taşkesen, Bahar; Besbinar, Beril; Koz, Alper; Alatan, A. Aydın

doi:10.1109/siu.2017.7960727

Cited by 2 publications

(1 citation statement)

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“…Mainly driven by the need in remote sensing, many algorithms have been proposed since 1980's, such as [1], [2]. Furthermore, applications of change detection include video surveillance [3]- [5], medical diagnosis and treatment [6]- [10], civil infrastructure [11], [12], under-water sensing [13]- [15], and driver assistance systems [16], [17]. In spite of different domains of application, the main task is to detect change in an image sequence with time order.…”

Section: Introductionmentioning

confidence: 99%

A Simple Change Comparison Method for Image Sequences Based on Uncertainty Coefficient

Zhao

Fang

Horn

2018

2018 4th International Conference on Universal Village (UV)

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For identification of change information in image sequences, most studies focus on change detection in one image sequence, while few studies have considered the change level comparison between two different image sequences. Moreover, most studies require the detection of image information in details, for example, object detection. Based on Uncertainty Coefficient(UC), this paper proposes an innovative method "CCUC" for change comparison between two image sequences. The proposed method is computationally efficient and simple to implement. The change comparison stems from video monitoring system. The limited number of provided screens and a large number of monitoring cameras require the videos or image sequences ordered by change level. We demonstrate this new method by applying it on two publicly available image sequences. The results are able to show the method can distinguish the different change level for sequences.

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