Towards relative gradient and its applications
Yang Wang, Hongzhi Liu, Zhonghai Wu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
Image gradients which present directional changes of pixel values in an image are widely considered as important clues for salient features like edges. However, it is difficult to distinguish edges from details which also have large gradients merely based on gradients. In this paper, we propose a novel model called relative gradient which can overcome the problem and better distinguish edges from flat regions and details. We demonstrate the effectiveness of our model by improving some representative algorithms using the relative gradient instead of traditional gradient in contexts of edge detection and non-linear filtering. More applications can be found in image processing, analysis and related tasks.