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首页> 外文学位 >Spectral distortion analysis in image fusion algorithms for remote sensing and development of fusion methods.
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Spectral distortion analysis in image fusion algorithms for remote sensing and development of fusion methods.

机译：遥感影像融合算法中的光谱失真分析和融合方法的发展。

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摘要

Image fusion in remote sensing is a technique that offers great promise and numerous algorithms have been developed to merge a high-spectral-resolution multispectral (MS) image with a high-spatial-resolution panchromatic (PAN) image in order to synthesize an image with the high spectral and spatial resolutions. One objective of image fusion is to synthesize images as close as possible to real images of the same spectral and spatial resolutions. Although the visualization and the spectral accuracy of synthetic images have been improved significantly, the spectral distortion in synthetic images is obvious and seriously impacts on the applications of the synthetic products. Except the main challenge of spectral distortion in current image fusion, several technical challenges still exist, including the limit on the spatial resolution ratio of MS and PAN images, automatic setting of parameters, and the impact of mis-registration of input MS and PAN images with a large spatial resolution difference. To solve these challenges, a series of solutions is proposed based on results of a thorough study on current image fusion techniques; in addition, each proposed fusion method performs well in preserving the spectral characteristics of MS images and sharpening visualization.;Atmospheric effects or haze, are rarely taken into account in current fusion methods. Taking haze into account, two improvements are proposed for a generalized ratio-based PAN modulation fusion method; taking haze into account and with reference to phenology of pixels, the third method significantly improves current multiresolution analysis-based fusion methods. The third method can fuse mixed MS sub-pixels optimally in the sense of probability. Mis-registration of MS and PAN images impacts on fusion quality seriously. Utilizing a direction similarity of the pixel vectors of each MS sub-pixel and neighbors, the fourth method effectively eliminates the impact of mis-registration on fusion.;The fusion of mixed MS sub-pixels is rarely addressed in image fusion and the corresponding synthetic pixels normally remain spectrally mixed and visually blurred. The fifth method may properly fuse mixed sub-pixels and significantly sharpen related soil-vegetation boundaries in synthetic products. Employing an object-oriented classification map of a PAN image, the sixth method can effectively fuse MS and PAN images with a significant spatial resolution ratio.;Thermal-IR and reflective images are normally too weakly correlated to be fused properly. Employing a technique of multivariate analysis, the seventh method can offer a synthetic thermal-IR image with high quality. Using a non-linear transform technique combined with a technique of multivariate analysis, the eighth method further improves fusion quality.
机译：遥感图像融合是一项具有广阔前景的技术，并且已开发出多种算法来将高光谱分辨率多光谱（MS）图像与高空间分辨率全色（PAN）图像融合在一起，从而通过高光谱和空间分辨率。图像融合的一个目标是合成图像，使其尽可能接近具有相同光谱和空间分辨率的真实图像。尽管合成图像的可视化和光谱精度已得到显着改善，但是合成图像中的光谱失真是明显的，并且严重影响了合成产品的应用。除了当前图像融合中频谱失真的主要挑战外，仍然存在一些技术挑战，包括对MS和PAN​​图像的空间分辨率的限制，参数的自动设置以及输入MS和PAN​​图像配准错误的影响具有较大的空间分辨率差异。为了解决这些挑战，基于对当前图像融合技术的深入研究结果，提出了一系列解决方案。此外，每种建议的融合方法在保留MS图像的光谱特征和锐化可视化方面都表现良好。；目前的融合方法很少考虑大气效应或雾度。考虑到雾度，针对基于比率的广义PAN调制融合方法提出了两种改进方法；考虑到雾度并参考像素物候，第三种方法显着改善了当前基于多分辨率分析的融合方法。从概率的意义上讲，第三种方法可以最佳地融合混合的MS子像素。 MS和PAN​​图像配准错误严重影响融合质量。第四个方法利用每个MS子像素和相邻像素的像素向量的方向相似性，有效地消除了配准错误对融合的影响。;在图像融合和相应的合成中很少解决混合MS子像素的融合问题。像素通常保持光谱混合并视觉模糊。第五种方法可以适当地融合混合的子像素，并显着锐化合成产品中的相关土壤植被边界。第六种方法是利用PAN图像的面向对象分类图，有效地融合具有显着空间分辨率的MS和PAN​​图像。热红外图像和反射图像之间的相关性通常太弱，无法正确融合。通过使用多元分析技术，第七种方法可以提供高质量的合成热红外图像。通过将非线性变换技术与多元分析技术相结合，第八种方法进一步提高了融合质量。

著录项

  • 作者

    Jing, Linhai.;

  • 作者单位

    York University (Canada).;

  • 授予单位 York University (Canada).;
  • 学科 Geotechnology.;Remote Sensing.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 238 p.
  • 总页数 238
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 地质学;遥感技术;
  • 关键词

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