Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Smoothing: A General Tool for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Color image processing and applications
Color image processing and applications
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Histogram Preserving Image Transformations
International Journal of Computer Vision
Mean Shift, Mode Seeking, and Clustering
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
Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised, Information-Theoretic, Adaptive Image Filtering for Image Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neighborhood filters and PDE’s
Numerische Mathematik
Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods
Image Processing And Analysis: Variational, Pde, Wavelet, And Stochastic Methods
Nonlocal Image and Movie Denoising
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A general framework for low level vision
IEEE Transactions on Image Processing
Color image enhancement via chromaticity diffusion
IEEE Transactions on Image Processing
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This paper presents an approach to image filtering that is driven by the properties of the iso-valued level curves of the image and their relationship with one another. We explore the relationship of our algorithm to existing probabilistically driven filtering methods such as those based on kernel density estimation, local-mode finding and mean-shift. Extensive experimental results on filtering gray-scale images, color images, gray-scale video and chromaticity fields are presented. In contrast to existing probabilistic methods, in our approach, the selection of the parameter that prevents diffusion across the edge is robustly decoupled from the smoothing of the density itself. Furthermore, our method is observed to produce better filtering results for the same settings of parameters for the filter window size and the edge definition.