1 |
Marpu, P. R., Gamba, P., and Canty, M. J. (2011), Improving change detection results of IR-MAD by eliminating strong changes, IEEE Geoscience and Remote Sensing Letters, Vol. 8, No. 4, pp. 799-803.
DOI
|
2 |
Nielsen, A. A. (2007), The regularized iteratively reweighted MAD method for change detection in multiand hyperspectral data, IEEE Transactions on Image Processing, Vol. 16, No. 2, pp. 463-478.
DOI
|
3 |
Park, N., Chi, K., Lee K., and Kwon, B. (2003), Automatic estimation of threshold values for change detection of multi-temporal remote sensing images, Korean Journal of Remote Sensing, Vol. 19, No. 6, pp. 465-478. (in Korean with English abstract)
DOI
|
4 |
Wang, B., Choi, S., Choi, J., and Yang, S. (2013), Comparison of change detection accuracy based on VHR images corresponding to the fusion estimation indexes, Journal of the Korean Society for Geospatial Information System, Vol. 21, No. 2, pp. 63-69. (in Korean with English abstract)
DOI
|
5 |
Wang, B., Choi, S., Byun, Y., Lee, S., and Choi, J. (2015a), Object-based change detection of very high resolution satellite imagery using the cross-sharpening of multitemporal data, IEEE Geoscience and Remote Sensing Letters, Vol. 12, No. 5, pp. 1151-1155.
DOI
|
6 |
Wang, B., Choi, S., Han, Y., Lee, S., and Choi, J. (2015b), Application of IR-MAD using synthetically fused images for change detection in hyperspectral data, Remote Sensing Letters, Vol. 6, No. 8, pp. 578-586.
DOI
|
7 |
Wu, C., Du, B., and Zhang, L. (2013), A subspace-based change detection method for hyperspectral images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 6, No. 2, pp.815-830.
DOI
|
8 |
Aleksandrowicz S., Turlej K., Lewiński S., and Bochenek Z. (2014), Change detection algorithm for the production of land cover change maps over the European Union Countries, Remote Sensing, Vol. 6, No. 7, pp. 5976-5994.
DOI
|
9 |
Byun, Y., Han, Y., and Chae, T. (2013), A multispectral image segmentation approach for objec-based image classification of high resolution satellite imagery, KSCE Journal of Civil Engineering, Vol. 17, No 2, pp. 486-497.
DOI
|
10 |
Choi. J. and Byun. Y. (2012), Effects analysis of the image fusion result by a relief displacement and changed area, in Proc. KSGPC, 2012, pp. 303–304.
|
11 |
Kim, D. and Kim, H. (2008), Automatic thresholding method using cumulative similarity measurement for unsupervised change detection of multispectral and hyperspectral images, Korean Journal of Remote Sensing, Vol. 24, No. 4, pp. 341-349. (in Korean with English abstract)
DOI
|
12 |
Carvalho Junior, O. A., Guimaraes, R. F., Gillespie, A. R., Silva, N. C., and Gomes, R. A. T. (2011), New approach to change vector analysis using distance and similarity measures, Remote Sensing, Vol. 3, No. 11, pp. 2473-2493.
DOI
|
13 |
Chen, G., Hay, G. J., Carvalho, L. M. T., and Wulder, M. A. (2012), Object-based change detection, International Journal of Remote Sensing, Vol. 33, No. 14, pp. 4434-4457.
DOI
|
14 |
Erturk, A. and Plaza, A. (2015), Informative change detection by unmixing for hyperspectral images, IEEE Geoscience and Remote Sensing Letters, Vol. 12, No. 6, pp. 1252-1256.
DOI
|
15 |
Marchesi, S., Bovolo, F., and Bruzzone, L. (2010), Context-sensitive technique robust to registration noise for change detection in VHR multispectral images, IEEE Transactions on Image Processing, Vol. 19, No. 7, pp. 1877-1889.
DOI
|