ICE WATER CLASSIFICATION USING STATISTICAL DISTRIBUTION BASED CONDITIONAL RANDOM FIELDS IN RADARSAT-2 DUAL POLARIZATION IMAGERY

In this paper, Statistical Distribution based Conditional Random Fields (STA-CRF) algorithm is exploited for improving marginal ice-water classification. Pixel level ice concentration is presented as the comparison of methods based on CRF. Furthermore, in order to explore the effective statistical d...

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Bibliographic Details
Published in:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Main Authors: Zhang, Y., Li, F., Zhang, S., Hao, W., Zhu, T., Yuan, L., Xiao, F.
Format: Text
Language:English
Published: 2018
Subjects:
Prydz Bay
Sea ice
Online Access:https://doi.org/10.5194/isprs-archives-XLII-2-W7-1585-2017
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/1585/2017/
Description
Summary:In this paper, Statistical Distribution based Conditional Random Fields (STA-CRF) algorithm is exploited for improving marginal ice-water classification. Pixel level ice concentration is presented as the comparison of methods based on CRF. Furthermore, in order to explore the effective statistical distribution model to be integrated into STA-CRF, five statistical distribution models are investigated. The STA-CRF methods are tested on 2 scenes around Prydz Bay and Adélie Depression, where contain a variety of ice types during melt season. Experimental results indicate that the proposed method can resolve sea ice edge well in Marginal Ice Zone (MIZ) and show a robust distinction of ice and water.

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