Model-based radiometric restoration

Russel P. Kauffman, P. North, P. M. Fuller
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Abstract

Radiance restoration via linear filtering is problematic for small targets, and estimating the thermally emitted radiance of sub-pixel targets is very difficult, resulting in large errors. However, with a priori knowledge of the geometry of a scene, a site model can be constructed to aid in radiance estimation. The scene is modeled as a linear combination of known shapes and the radiance of these shapes is adjusted to fit the observed image. This method of estimating the radiances of small to sub-pixel targets can yield significantly lower errors than linear filtering. The performance of the method on synthetic images is discussed as a function of the size, radiance, and background of the target and of the noise in the image. The model-based approach is found to outperform a simple linear filter for very small targets (diameter of a few pixels) with high contrast relative to the image noise.1 2
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基于模型的辐射恢复
对于小目标,线性滤波的辐射恢复存在问题,而亚像元目标的热发射辐射估计非常困难,误差很大。然而,有了先验的几何知识的场景,可以构建一个站点模型,以帮助在辐射估计。将场景建模为已知形状的线性组合,并调整这些形状的亮度以适应观察到的图像。这种估计小到亚像素目标辐射度的方法比线性滤波产生的误差要小得多。讨论了该方法在合成图像上的性能与目标的大小、亮度、背景和图像中的噪声有关。对于相对于图像噪声具有高对比度的非常小的目标(几个像素的直径),发现基于模型的方法优于简单的线性滤波器。1 2
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