基于目标的图像融合在高分辨率卫星图像中实现颜色失真最小化

Munmun Baisantry, D. Negi, O. P. Manocha, Bhanu Pratap Singh, Sandeep Kishore
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引用次数: 5

摘要

色彩或光谱失真是图像融合领域的一个重要问题。在高分辨率卫星图像中,由于全色波段和质谱波段的光谱不匹配,这一问题更为普遍。目前基于像素的技术还不能很好地处理这个问题。此外,这些技术没有考虑图像中各种物体的空间、光谱或辐射特征,所有像素都是用同一准则融合的。为了使应用程序更接近现实场景,本文提出了一种更真实、自调节、基于属性的面向对象融合范式。在不同的层次上考虑了不同的目标属性,以最小的光谱失真将更多的空间细节嵌入到低分辨率MSS图像中。定量评价指标的计算也证明了我们的方法在最小化色彩失真和最大化空间细节方面优于其他方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Object-based image fusion for minimization of color distortion in high-resolution satellite imagery
Color or spectral distortion is a serious issue in the field of Image Fusion. The problem is more prevalent in high-resolution satellite imagery due to spectral mismatching of panchromatic and MS bands. Current pixel-based techniques are not well-equipped to handle the problem. Moreover, these techniques do not consider the spatial, spectral or radiometric characteristics of various objects in the image and all the pixels are fused with the same criterion. To bring the application closer to the real-world scene, a more realistic, self-adjustable, attribute-based object-oriented paradigm towards fusion has been proposed in the paper. Various objects attributes have been considered at different levels to embed greater spatial details into the low resolution MSS image with minimum spectral distortion. Quantitative assessment indices have also been calculated to prove that our method is superior in terms of minimization of color distortion and maximization of spatial details as compared to other methods.
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