Sea ice classification using multi-frequency polarimetric SAR data
Sea ice classification using multi-frequency polarimetric SAR data
复制标题
使用多频极化 SAR 数据进行海冰分类
DOI：
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
I. Cumming
中科院分区：
文献类型：
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作者：
B. Scheuchl;I. Hajnsek;I. Cumming
本文讨论了复杂的Wishart分类海冰和分类使用多频，全极化SAR数据的能力。使用了JPL AIRSAR在博福特海获得的C、L和P波段数据。使用无监督Wishart分类器的分类是一个两阶段的过程。初始分类需要种子算法，可以使用其他分类方法导出。Wishart分类器然后用于迭代，其中类均值在每一步之后更新。这种方法的收敛性进行了研究。Wishart分类器被发现是非常占主导地位的，使得几次迭代后的分类结果不一定取决于用于导出第一类均值的初始分类。即使是用随机数生成器导出的初始分类，在几次迭代之后也会产生良好的结果。
This paper discusses the capability of the complex Wishart classifier for sea ice and classification using multifrequency, fully polarimetric SAR data. C-, L-, and P-band data acquired by the JPL AIRSAR in the Beaufort Sea was used. Classification using the unsupervised Wishart classifier is a two-stage process. An initial classification is required to seed the algorithm and can be derived using other classification methods. The Wishart classifier then used in iterations where the class means are updated after every step. The convergence of this approach is investigated. The Wishart classifier was found to be extremely dominant so that the classification result after a few iterations depends not necessarily on the initial classification used to derive the first class means. Even an initial classification derived with a random number generator leads to a good result after a few iterations.