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An image segmentation variational model with free discontinuities and contour curvature

机译:具有自由间断和轮廓曲率的图像分割变分模型

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摘要

We introduce a functional for image segmentation which takes into account the transparencies (or shadowing) and the occlusions between objects located at different depths in space. By minimizing the functional, we try to reconstruct a piecewise smooth approximation of the input image, the contours due to transparencies, and the contours of the objects together with their hidden portions. The functional includes a Mumford-Shah type energy and a term involving the curvature of the contours. The variational properties of the functional are studied, as well as its approximation by Gamma-convergence. The comparison with the Nitzberg-Mumford variational model for segmentation with depth is also discussed.
机译:我们介绍了一种用于图像分割的功能,该功能考虑了位于空间不同深度处的对象之间的透明度(或阴影)和遮挡。通过最小化功能,我们尝试重建输入图像,由于透明胶片引起的轮廓以及对象的轮廓及其隐藏部分的分段平滑逼近。该函数包括Mumford-Shah型能量和涉及轮廓曲率的项。研究了泛函的变分性质,以及它的伽玛收敛近似。还讨论了与Nitzberg-Mumford变分模型进行深度分割的比较。

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