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Multiscale differential fractal feature with application to target detection

机译:多尺度差分分形功能,具有瞄准检测的应用

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A multiscale differential fractal feature of an image is proposed and a small target detection method from complex nature clutter is presented. Considering the speciality that the fractal features of man-made objects change much more violently than that of nature's when the scale is varied, fractal features at multiple scales used for distinguishing man-made target from nature clutter should have more advantages over standard fractal dimensions. Multiscale differential fractal dimensions are deduced from typical fractal model and standard covering-blanket method is improved and used to estimate multiscale fractal dimensions. A multiscale differential fractal feature is defined as the variation of fractal dimensions between two scales at a rational scale range. It can stand out the fractal feature of man-made object from natural clutters much better than the fractal dimension by standard covering-blanket method. Meanwhile, the calculation and the storage amount are reduced greatly, they are 4/M and 2/M that of the standard covering-blanket method respectively (M is scale). In the image of multiscale differential fractal feature, local gray histogram statistical method is used for target detection. Experiment results indicate that this method is suitable for both kinds background of land and sea. It also can be appropriate in both kinds of infrared and TV images, and can detect small targets from a single frame correctly. This method is with high speed and is easy to be implemented.
机译:提出了一种图像的多尺度差分分形特征,并提出了来自复杂性质杂波的小目标检测方法。考虑到专长,人造物体的分形特征比大自然变化更剧烈的变化更加剧烈,当规模变化时,用于区分自然杂波的人造目标的多个尺度的分形特征应具有更多的优于标准分形尺寸。从典型的分形模型推断多尺度差分分形尺寸,并改进标准覆盖毯方法,用于估计多尺度分形尺寸。多尺度差分分形特征被定义为在Rational刻度范围内的两种尺度之间的分数尺寸的变化。它可以通过标准覆盖毯法从分形尺寸脱颖而出人造物体的分形特征。同时,计算和存储量大大减少,分别是标准覆盖毯方法的4 / m和2 / m(M是刻度)。在多尺度差分分形特征的图像中,局部灰色直方图统计方法用于目标检测。实验结果表明,该方法适用于陆地和海洋的两种。它还可以适用于两种红外和电视图像,并且可以正确地从单个帧中检测小目标。这种方法具有高速,易于实现。

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