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Numrering	Referens	Omslagsbild	Hitta
1.	Javadi, Mohammad Saleh, 1986-, et al. (författare) Change detection in aerial images using a Kendall's TAU distance pattern correlation 2016 Ingår i: PROCEEDINGS OF THE 2016 6TH EUROPEAN WORKSHOP ON VISUAL INFORMATION PROCESSING (EUVIP). - : IEEE. - 9781509027811 Konferensbidrag (refereegranskat)abstract Change detection in aerial images is the core of many remote sensing applications to analyze the dynamics of a wide area on the ground. In this paper, a remote sensing method is proposed based on viewpoint transformation and a modified Kendall rank correlation measure to detect changes in oblique aerial images. First, the different viewpoints of the aerial images are compromised and then, a local pattern descriptor based on Kendall rank correlation coefficient is introduced. A new distance measure referred to as Kendall's Tau-d (Tau distance) coefficient is presented to determine the changed regions. The developed system is applied on oblique aerial images with very low aspect angles that obtained using an unmanned aerial vehicle in two different days with drastic change in illumination and weather conditions. The experimental results indicate the robustness of the proposed method to variant illumination, shadows and multiple viewpoints for change detection in aerial images.

Javadi, Mohammad Saleh, 1986-, et al. (författare)
Change detection in aerial images using a Kendall's TAU distance pattern correlation
2016
Ingår i: PROCEEDINGS OF THE 2016 6TH EUROPEAN WORKSHOP ON VISUAL INFORMATION PROCESSING (EUVIP). - : IEEE. - 9781509027811
Konferensbidrag (refereegranskat)abstract
- Change detection in aerial images is the core of many remote sensing applications to analyze the dynamics of a wide area on the ground. In this paper, a remote sensing method is proposed based on viewpoint transformation and a modified Kendall rank correlation measure to detect changes in oblique aerial images. First, the different viewpoints of the aerial images are compromised and then, a local pattern descriptor based on Kendall rank correlation coefficient is introduced. A new distance measure referred to as Kendall's Tau-d (Tau distance) coefficient is presented to determine the changed regions. The developed system is applied on oblique aerial images with very low aspect angles that obtained using an unmanned aerial vehicle in two different days with drastic change in illumination and weather conditions. The experimental results indicate the robustness of the proposed method to variant illumination, shadows and multiple viewpoints for change detection in aerial images.

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