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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Multispectral Remote Sensing Image Matching via Image Transfer by Regularized Conditional Generative Adversarial Networks and Local Feature
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Multispectral Remote Sensing Image Matching via Image Transfer by Regularized Conditional Generative Adversarial Networks and Local Feature

机译：通过正则化条件生成对策网络和本地特征通过图像传输匹配多光谱遥感图像

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摘要

Multispectral image matching is at the base for many remote sensing and computer vision applications. Due to the different imaging principles and spectra, there are significant nonlinear variations in intensity, texture, and style in multispectral images. This makes it difficult for many classic methods designed for the images of the same spectrum to achieve satisfactory matching performance. To cope with this problem, this letter proposes a new method based on image transfer and local feature for multispectral image matching. First, we propose a new regularized conditional generative adversarial network (GAN) for image transfer to preprocess the multispectral images. This step eliminates the differences in grayscale, texture, and style between the multispectral images. Then, we use a classic local feature to match the generated and original images. We evaluate our method on two commonly used data sets and compare with several state-of-the-art methods. The experiments show that our method performs well by significantly improving the matching accuracy and robustness, and slightly increasing the runtime.
机译：多光谱图像匹配在许多遥感和计算机视觉应用程序的基础上。由于不同的成像原理和光谱，多光谱图像中的强度，纹理和样式存在显着的非线性变化。这使得许多经典方法难以为相同频谱的图像设计以实现令人满意的匹配性能。要应对这个问题，这封信提出了一种基于图像传输和本地特征的新方法，用于多光谱图像匹配。首先，我们提出了一种新的正则化条件生成的对抗网络（GaN），用于图像传输以预处理多光谱图像。此步骤消除了多光谱图像之间的灰度，纹理和样式的差异。然后，我们使用经典的本地功能来匹配生成和原始图像。我们在两个常用的数据集上评估我们的方法，并与多种最先进的方法进行比较。实验表明，我们的方法通过显着提高匹配的准确性和鲁棒性，并略微增加运行时来表现良好。

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  • 来源
    《IEEE Geoscience and Remote Sensing Letters》 |2021年第2期|351-355|共5页
  • 作者

    Tao Ma; Jie Ma; Kun Yu; Jun Zhang; Wenxing Fu;

  • 作者单位

    National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China;

    National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China;

    National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China;

    National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China;

    Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Gallium nitride; Generative adversarial networks; Generators; Remote sensing; Image matching; Feature extraction; Robustness;

    机译：氮化镓;生成的对抗网络;发电机;遥感;图像匹配;特征提取;鲁棒性;

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