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Spectral Characteristics Analysis of the Hyperspectral Image

机译:高光谱图像的光谱特征分析

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摘要

Hyper-spectral image is a group of remote sensing images with relatively high correlation. Comprehensive analyses of the image features will help us to design better image compression algorithm. By using visualization method, this paper more comprehensively researched the characteristics of hyper-spectral image from the perspectives of spectral correlation, mutual information and change of pixel value. We find that quantification does not change the characteristics of images. The correlate coefficients and the normalized mutual information of the hyper-spectral images are higher when the distance of bands is smaller. The proportion of large change of pixel values is less than 1%. These analyses provided theoretical support for hyper-spectral image compression.
机译:高光谱图像是一组具有较高相关性的遥感图像。对图像特征的全面分析将有助于我们设计更好的图像压缩算法。通过使用可视化方法,从光谱相关性,互信息和像素值变化的角度对高光谱图像的特征进行了更全面的研究。我们发现量化不会改变图像的特征。当频带的距离较小时,高光谱图像的相关系数和归一化互信息较高。像素值的大变化比例小于1%。这些分析为高光谱图像压缩提供了理论支持。

著录项

  • 来源
    《Journal of information and computational science》 |2015年第11期|4299-4308|共10页
  • 作者单位

    School of Mechanical Electrical and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;

    School of Mechanical Electrical and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;

    School of Mechanical Electrical and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;

    School of Mechanical Electrical and Information Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Prediction; Spectral Correlation; Variation of Pixel;

    机译:预测;频谱相关像素变化;

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