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.

Date Published: 4 March 2015
PDF: 5 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94432Z (4 March 2015); doi: 10.1117/12.2179516

Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)