In image processing, it can be a useful pre-processing step to smooth away smallstructures, such as noise or unimportant details, while retaining the overall structure of the imageby keeping edges, which separate objects, sharp. Typically this edge-preserving smoothing processis achieved using edge-aware filters. However such filters may preserve unwanted small structures aswell if they contain edges. In this work we present a novel framework for edge-preserving smoothingwhich separates the process into two different steps: First the image is smoothed using a blurringfilter and in the second step the important edges are restored using a guided edge-aware filter. Thepresented method proves to deliver very good results, compared to state-of-the-art edge-preservingsmoothing filters, especially at removing unwanted small structures. Furthermore it is very versatileand can easily be adapted to different fields of applications while at the same time being very fastto compute and therefore well-suited for real time applications.


Kniefacz, P., & Kropatsch, W. (2015). Smooth and iteratively restore: A simple and fast edge-preserving smoothing model. In A. Uhl & R. Kwitt (Eds.), Proceedings of the ÖAGM Workshop 2015, Salzburg, Austria, May 2015 (p. 9). http://hdl.handle.net/20.500.12708/55194