基于EM算法的多极化ALOS PALSAR图像融合土地覆盖分类

2013 International Conference on Microwave and Photonics (ICMAP) Pub Date : 2013-12-01 DOI:10.1109/ICMAP.2013.6733503

Vikas Mittal, D. Singh, L. Saini

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引用次数: 2

摘要

本文尝试利用融合技术来提高图像的信息质量，从而使其得到更有效的利用。利用期望最大化(EM)算法的优点，对ALOS PALSAR全极化图像进行融合。将最大似然分类器应用于融合单线和融合双线复合图像，并从生产者、使用者、整体精度和Kappa系数等方面对结果进行比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Land cover classification using EM algorithm based multi-polarized ALOS PALSAR image fusion

In this paper, an attempt has been made to improve information of an image by fusion technique, so it may be more effectively used. Full polarimetric images of ALOS PALSAR are fused by exploiting the nice properties of Expectation Maximization (EM) algorithm. Maximum likelihood classifier is applied on the composite unfused singlet and fused doublet images and results are compared on the basis of producer, user, overall accuracies and Kappa Coefficient.

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来源期刊

2013 International Conference on Microwave and Photonics (ICMAP)

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