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A hypothesis independent subpixel target detector for hyperspectral Images

机译:假设独立的高光谱图像亚像素目标检测器

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In previous work, the statistical characteristics of the background or the noise under H_0 hypothesis are similar as that under H, hypothesis. Accordingly, the parameters under both hypotheses are estimated by the maximum likelihood method and finally a generalized likelihood ratio test based detector is developed, such as the matched subspace detector. Unfortunately, this kind of statistical similarity for both hypotheses may be changing, which is directly related to the unknown beforehand target fill factor. A hypothesis independent method is proposed to solve this problem, which uses different approaches to estimate the parameters for different hypotheses. Experiments on simulated data and real hyperspectral image demonstrate the ability of this proposed detector for subpixel target detection.
机译:在先前的工作中,H_0假设下的背景或噪声的统计特征与H,假设下的背景或噪声的统计特征相似。因此,通过最大似然法估计两个假设下的参数,最后开发出基于广义似然比测试的检测器,例如匹配子空间检测器。不幸的是,这两种假设的统计相似性可能正在改变,这与未知的预先目标填充因子直接相关。提出了一种假设独立的方法来解决这个问题,该方法使用不同的方法来估计不同假设的参数。在模拟数据和真实高光谱图像上进行的实验证明了该探测器可用于亚像素目标检测。

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