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Using Renyi's information and Wavelets for Target Detection: An Application to Mammograms

机译:利用人一的信息和小波进行目标检测:在乳腺X线照片中的应用

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In this paper we present a multi-scale method for the detection of small targets embedded in noisy background. The multi- scale representation is built using a weighted undecimated discrete wavelet transform. The method, in essence, is based on the maximization of information available at each resolution level of the representation. We show that such objective can be achieved by maximizing Renyi's information. This approach allows us to determine an adaptive threshold useful for discriminating, at each scale, between wavelet Coefficients representing targets and those representing background noise. Eventually, avoiding inverse transformation, scale-dependent Estimates are combined according to a majority vote strategy. The proposed technique is experimented on a standard data set of Mammographic images.
机译:在本文中,我们提出了一种用于检测嵌入噪声背景中的小目标的多尺度方法。使用加权的未抽取离散小波变换构建多尺度表示。本质上,该方法是基于表示的每个分辨率级别上可用信息的最大化。我们表明,通过最大化仁义的信息可以实现这一目标。这种方法使我们能够确定一个自适应阈值,该阈值可用于在各个尺度上区分代表目标的小波系数和代表背景噪声的小波系数。最终,为了避免逆变换,将根据多数表决策略合并与比例相关的估计。所提出的技术在乳房X线照片的标准数据集上进行了实验。

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