Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Viscous Watershed Transform
Journal of Mathematical Imaging and Vision
Theoretical Foundations of Spatially-Variant Mathematical Morphology Part II: Gray-Level Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Upper and Lower Grey-Level Adaptive Morphological Operators
ICAPR '09 Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition
Morphological operators on the unit circle
IEEE Transactions on Image Processing
Flat zones filtering, connected operators, and filters by reconstruction
IEEE Transactions on Image Processing
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The aim of this study is to propose an algorithm for simplifying color images. The assumption is made that a set of reference colors is available and that this set indicates which features are of importance in the image. The goal is then to simplify as much as possible the color image while preserving as much as possible the shapes that are similar to the reference set. The proposed algorithm is in two steps. In a first step, a scalar similarity image of same morphological structure as the color image is computed. This allows to associate similarity-level sets with the color image that are used, in the second step, for performing a similarity-adaptive simplification of the color image: each similarity-level set is associated with a certain filter, the filtering parameter being a decreasing function of the similarity.