Gradient-Based Segmentation Requires Doubling of the Sampling Rate
Ullrich Köthe · 2003
We apply Shannon's sampling theorem to gradient based image segmentation and show that the gradient magnitude requires twice the sampling rate of the original image. Taking this simple, but apparently overlooked phenomenon into account, we demonstrate experimentally that correct sampling of the gradient image indeed improves the quality of the resulting segmentation.