Title :
A Riemannian Weighted Filter for Edge-sensitive Image Smoothing
Author :
Zhang, Fan ; Hancock, Edwin R.
Author_Institution :
Dept. of Comput. Sci., York Univ.
Abstract :
This paper describes a new method for image smoothing. We view the image features as residing on a differential manifold, and we work with a representation based on the exponential map for this manifold (i.e. the map from the manifold to a plane that preserves geodesic distances). On the exponential map we characterise the features using a Riemannian weighted mean. We show how both gradient descent and Newton´s method can be used to find the mean. Based on this weighted mean, we develop an edge-preserving filter that combines Gaussian and median filters of gray-scale images. We demonstrate our algorithm both on direction fields from shape-from-shading and tensor-valued images
Keywords :
Newton method; gradient methods; image representation; smoothing methods; Gaussian filter; Newton method; Riemannian weighted filter; differential manifold; edge-preserving filter; edge-sensitive image smoothing; gradient descent method; median filter; Computer science; Diffusion tensor imaging; Filters; Gray-scale; Harmonic analysis; Magnetic analysis; Magnetic resonance; Magnetic separation; Smoothing methods; Tensile stress;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.162