A novel real-time edge-preserving smoothing filter
Document typeConference report
Rights accessOpen Access
The segmentation of textured and noisy areas in images is a very challenging task due to the large variety of objects and materials in natural environments, which cannot be solved by a single similarity measure. In this paper, we address this problem by proposing a novel edge-preserving texture filter, which smudges the color values inside uniformly textured areas, thus making the processed image more workable for color-based image segmentation. Due to the highly parallel structure of the method, the implementation on a GPU runs in realtime, allowing us to process standard images within tens of milliseconds. By preprocessing images with this novel filter before applying a recent real-time color-based image segmentation method, we obtain significant improvements in performance for images from the Berkeley dataset, outperforming an alternative version using a standard bilateral filter for preprocessing. We further show that our combined approach leads to better segmentations in terms of a standard performance measure than graph-based and mean-shift segmentation for the Berkeley image dataset.
CitationReich, S. [et al.]. A novel real-time edge-preserving smoothing filter. A: International Conference on Computer Vision Theory and Applications. "VISAPP 2013 - Proceedings of the International Conference on Computer Vision Theory and Applications". Barcelona: 2013, p. 1-11.