Wang, Z., F. Meng, X. Yang, F. Yang, and Y. Fang, 2016. Study on
the automatic selection of segmentation scale parameters for
high spatial resolution remote sensing images,
Journal of Geo-
information Science
, 18(5):639-648.
Weidner, U., 2008. Contribution to the assessment of segmentation
quality for remote sensing applications,
International Archives
of Photogrammetry, Remote Sensing and Spatial Information
Sciences
, 37(B7):479-484.
Weszka, J.S., and A. Rosenfeld, 1978. Threshold evaluation
techniques,
IEEE Transactions on Systems, Man, and
Cybernetics
, 8(8):622-629.
Wong, A.K., and P.K. Sahoo, 1989. A gray-level threshold
selection method based on maximum entropy principle,
IEEE
Transactions on Systems, Man, and Cybernetics
, 19(4):866-871.
Woodcock, C.E., and A.H. Strahler, 1987. The factor of scale in remote
sensing,
Remote sensing of Environment
, 21(3):311-332.
Wulder, M., R. Hall, N. Coops, and S. Franklin, 2004. High spatial
resolution remotely-sensed data for the study of forest
ecosystems,
Bioscience
, 54:511-521.
Yang, J., P. Li, and Y. He, 2014. A multi-band approach to
unsupervised scale parameter selection for multi-scale image
segmentation,
ISPRS Journal of Photogrammetry and Remote
Sensing
, 94:13-24.
Yang, J., Y. He, J. Caspersen, and T. Jones, 2015a. A discrepancy
measure for segmentation evaluation from the perspective
of object recognition,
ISPRS Journal of Photogrammetry and
Remote Sensing
, 101:186-192.
Yang, J., Y. He, and Q. Weng, 2015b. An automated method to
parameterize segmentation scale by enhancing intrasegment
homogeneity and intersegment heterogeneity,
IEEE Geoscience
and Remote Sensing Letters
, 12(6):1282-1286.
Yang, L., F. Albregtsen, T. Lønnestad, and P. Grøttum, P., 1995. A
supervised approach to the evaluation of image segmentation
methods,
Proceedings of the Sixth International Conference on
Computer Analysis of Images and Patterns
, 06-08 September
1995, Prague, Czech Republic (Springer), pp. 759-765.
Yu, H., S. Zhang, B. Kong, and X. Li, 2010. Optimal segmentation
scale selection for object-oriented remote sensing image
classification,
Journal of Image and Graphics
, 15(2):352-360.
Yu, Q., P. Gong, N. Clinton, G. Biging, M. Kelly, and D. Schirokauer,
2006. Object-based detailed vegetation classification with
airborne high spatial resolution remote sensing imagery,
Photogrammetric Engineering & Remote Sensing
, 72(7):799-811.
Zéboudj, R., 1988.
Filtrage, seuillage automatique, contraste
et contours: du pré-traitement à l‘analyse d‘image
, Ph.D.
dissertation, Université de Saint-Etienne, Saint-Etienne,
Zhan, Q., M. Molenaar, K. Tempfli, and W. Shi, 2005. Quality
assessment for geo‐spatial objects derived from remotely sensed
data,
International Journal of Remote Sensing
, 26(14):2953-2974.
Zhang, H., J.E. Fritts, and S.A. Goldman, 2004. An entropy-based
objective evaluation method for image segmentation,
Storage
and Retrieval Methods and Applications for Multimedia
,
5307:38-49.
Zhang, H., J.E. Fritts, and S.A. Goldman, 2008. Image segmentation
evaluation: A survey of unsupervised methods,
Computer Vision
and Image Understanding
, 110(2):260-280.
Zhang, J., G.-L. Zhu, and F. Li, 2011. Scale effect and optimal scale in
object-oriented information extraction of high spatial resolution
remote sensing image,
Science of Surveying and Mapping
,
36(2):107-109.
Zhang, J., L. Zhang, and T. Xu, 2015a. Heterogeneity measure based
segmentation performance evaluation for remote sensing image,
Journal of Geomatics Science and Technology
, 32(5):479-482.
Zhang, Q., G. Pavlic, W., Chen, R. Fraser, S. Leblanc, and J. Cihlar,
J., 2005. A semi-automatic segmentation procedure for
feature extraction in remotely sensed imagery,
Computers &
Geosciences
, 31(3):289-296.
Zhang, S., J. Dong, and L. She, 2009. The methodology of evaluating
segmentation algorithms on medical image,
Journal of Image and
Graphics
, 14(9):1872-1880.
Zhang, X., X. Feng, P. Xiao, G. He, and L. Zhu, 2015b. Segmentation
quality evaluation using region-based precision and recall
measures for remote sensing images,
ISPRS Journal of
Photogrammetry and Remote Sensing
, 102:73-84.
Zhang, X., and D. Ming, 2015. Geo-application oriented evaluations
of remote sensing image segmentation,
Acta Geodaetica et
Cartographica Sinica
, 44(S0):108-116.
Zhang, X., P. Xiao, X. Feng, L. Feng, and N. Ye, 2015c. Toward
evaluating multiscale segmentations of high spatial resolution
remote sensing images,
IEEE Transactions on Geoscience and
Remote Sensing
, 53(7):3694-3706.
Zhang, Y., 1996a. A survey on evaluation methods for image
segmentation,
Pattern Recognition
, 29(8):1335-1346.
Zhang, Y., 1996b. A classification and comparison of evaluation
techniques for image segmentation,
China Journal of Image and
Graphics
, 1(2):151-158.
Zhang, Y., 2001. A review of recent evaluation methods for
image segmentation,
Proceedings of the Sixth International,
Symposium on Signal Processing and its Applications
, 13-
16 August 2001, Kuala Lumpur, Malaysia (Department of
Microelectronics and Computer Engineering), pp. 148-151.
Zhao, L., E. Chen, Z. Li, Q. Feng,L. Li, and H. Yang, 2015.
Segmentation of PolSAR data based on mean-shift and
spectral graph partitioning and its evaluation,
Geomatics and
Information Science of Wuhan University
, 40(8):1061-1068.
Zhao, M., F. Li, and G.A.Tang, 2012. Optimal scale selection for DEM
based slope segmentation in the loess plateau,
International
Journal of Geosciences
, 3(1):37.
646
October 2018
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING