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A non-Newtonian gradient for contour detection in images with multiplicative noise

机译:非牛顿梯度在乘性噪声图像中的轮廓检测

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摘要

In this paper, a new operator for contour detection in images with multiplicative noise is presented. Traditional methods of edge detection, as those based in gradient operator or measures of variance, follow a logic and a math formulation in correspondence with the Differential and Integral Calculus of Newton. This work presents a new operator of non-Newtonian type which had shown be more efficient in contour detection than the traditional operators. Like the regular gradient, a non-Newtonian gradient can be used in a number of more complex methods, which shows its potential in the contours detection in images affected by multiplicative noise.
机译:在本文中,提出了一种在带乘性噪声的图像中进行轮廓检测的新算子。传统的边缘检测方法(例如基于梯度算子或方差测量的方法)遵循与牛顿微分和积分算法相对应的逻辑和数学公式。这项工作提出了一种新的非牛顿算子,它在轮廓检测中比传统算子更有效。像常规梯度一样,非牛顿梯度可以用在许多更复杂的方法中,这在受乘法噪声影响的图像的轮廓检测中显示了其潜力。

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