快速尺度空间图像分解

A. Alsam, H. J. Rivertz
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引用次数: 0

摘要

在保留边缘的同时从图像中去除高频是一个复杂的问题,在文献中有许多解决方案。然而,这些解决方案中的大多数都是迭代的,并且计算成本很高。本文介绍了一种包含三个基本步骤的直接法。在第一种方法中,图像与一个定义大小的高斯函数进行卷积。在第二种方法中,将模糊图像的梯度与原始图像的梯度进行比较,并组成第三个梯度,该梯度是两个梯度在每个像素处的最小值。最后在傅里叶域中对组合梯度进行积分得到结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast scale space image decomposition
The removal of high frequencies from an image while retaining edges, is a complicated problem that has many solutions in the literature. Most of these solutions are, however, iterative and computationally expensive. In this paper, we introduce a direct method with three basic steps. In the first, the image is convolved with a Gaussian function of a defined size. In the second the gradients of the blurred image are compared with those of the original and a third gradient that is the minimum of the two at each pixel is composed. Finally, the combined gradient is integrated in the Fourier domain to obtain the result.
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