TY - GEN
T1 - Sea-Ice Classification Based on Optical Image Using Morphological Profile Features
AU - Zhou, Yuchan
AU - Li, Wei
AU - Ren, Peng
AU - Li, Zhongwei
AU - Tao, Ran
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/26
Y1 - 2020/9/26
N2 - Sea-ice classification plays an important role in evaluating sea-ice hazards and ensuring maritime safety. In this paper, a method of sea-ice classification based on morphological feature extraction is proposed by using CEBRS-02B multispectral CCD image. The paper uses local contain profile (LCP) to extract morphological features of the multispectral image. Then SVM- and MRF- (SVMMRF) is adopted, which including probabilistic support vector machine (SVM) for the preliminary classification of multispectral image, the postprocessing by using Markov random field (MRF) based regularization. Experimental results demonstrate the validity of the classification model framework is applied to sea-ice classification. Compared with the traditional Local Binary Pattern (LBP) and Gabor, feature extraction by LCP can improve the accuracy of sea-ice classification.
AB - Sea-ice classification plays an important role in evaluating sea-ice hazards and ensuring maritime safety. In this paper, a method of sea-ice classification based on morphological feature extraction is proposed by using CEBRS-02B multispectral CCD image. The paper uses local contain profile (LCP) to extract morphological features of the multispectral image. Then SVM- and MRF- (SVMMRF) is adopted, which including probabilistic support vector machine (SVM) for the preliminary classification of multispectral image, the postprocessing by using Markov random field (MRF) based regularization. Experimental results demonstrate the validity of the classification model framework is applied to sea-ice classification. Compared with the traditional Local Binary Pattern (LBP) and Gabor, feature extraction by LCP can improve the accuracy of sea-ice classification.
KW - Markov random field (MRF)
KW - morphological profile
KW - multispectral image (MSI)
KW - sea-ice classification
UR - https://www.scopus.com/pages/publications/85101978212
U2 - 10.1109/IGARSS39084.2020.9323480
DO - 10.1109/IGARSS39084.2020.9323480
M3 - Conference contribution
AN - SCOPUS:85101978212
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 3055
EP - 3058
BT - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Y2 - 26 September 2020 through 2 October 2020
ER -