Urban-Area and Building Detection Using SIFT Keypoints and Graph Theory

Detection of incomplete enclosures of rectangular shape in remotely sensed images

“…Examples are detection of buildings in remotely sensed images [24,19,14,3,12,15,1,31,30,23,26], traffic signs [21,13,22], and particles of a rectangular shape in cryo-electron microscopy images [36,35]. The methods used were based on Markov Random Fields [15,21], Marked Point Processes [1,26], search on a graph [14,38], Hough Transform and other voting schemes [3,12,36,13,22], template matching [25], aggregation of local features [1,23,31], and heuristic rules [19].…”

Development and Evaluation of a Texture-Based Urban Change Detection Method Using Very High Resolution SAR Imagery

“…Incoherent 변화탐 지기법은 SAR영상의 진폭값만을 이용하는 방법을 말 하며 대표적인 기법으로는 NCCD, Correlation, 로그비 기법 등이 있다 (Liu et al, 2011) (Dellinger et al, 2014;Sirmacek et al, 2009) (He et al, 2010). 텍스처는 SAR 영상의 고유한 공간적인 변동성을 다루는데 이것 Korean Journal of Remote Sensing, Vol.31, No.3, 2015 -2 56 - …”

Scale Invariant Feature Transform on the Sphere: Theory and Applications

“…The size of this region depends on the scale at which the point has been detected. Thanks to its simplicity, good results in terms of repeatability and accuracy on matching, it has been used to treat applications requiring tracking or matching of regions (Sirmacek and Unsalan 2009;Brox et al 2010). Several variants of the SIFT algorithm have appeared, trying to improve the interest point extraction or the local descriptor.…”