Visual reconstruction
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
Digital Picture Processing
Visual Information Representation, Communication, and Image Processing
Visual Information Representation, Communication, and Image Processing
Bilateral Filtering for Gray and Color Images
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Non-Rigid Motion Estimation Using the Robust Tensor Method
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 1 - Volume 01
Adaptive robust structure tensors for orientation estimation and image segmentation
ISVC'05 Proceedings of the First international conference on Advances in Visual Computing
Behavioral analysis of anisotropic diffusion in image processing
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Markovian reconstruction using a GNC approach
IEEE Transactions on Image Processing
Image denoising using scale mixtures of Gaussians in the wavelet domain
IEEE Transactions on Image Processing
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Image smoothing is a critical preprocessing step in many image processing tasks. In this paper, a generalized edge-preserving smoothing model is derived from robust statistics theory, and its connections to anisotropic diffusion and bilateral filtering are established. The relationships allow us to derive an improved numerical scheme in the context of a robust estimation process for edge preserving smoothing. Experiments illustrate that the proposed smoothing algorithm is capable of effectively reducing the distracting effects of noise without sacrificing image edge structures. The robust edge-preserving smoothing method performs several dB better in terms of PSNR compared to anisotropic diffusion, bilateral filtering and the Bayes least squares Gaussian scale mixtures a wavelet-based methods for image enhancement.