Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Algorithm for Data-Driven Bandwidth Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Gaussian Mean-Shift Is an EM Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion-based background subtraction using adaptive kernel density estimation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
On the origin of the bilateral filter and ways to improve it
IEEE Transactions on Image Processing
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This paper evaluates the effectiveness of the multiscale mode filters (MSMF) in edge preserving image smoothing tasks. The MSMF can be viewed as a generalization of the mean shift filters. Therefore, the performances of the MSMF are compared with the performances of the mean shift filters. The goal of the study is to identify image types where the MSMF can be used with better results and to quantify the gain obtained by this filter. Compared with the conventional mean shift filter, the MSMF is proven to be most effective in restoring images with blurred edges and high noise levels.