A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Attribute openings, thinnings, and granulometries
Computer Vision and Image Understanding
Generalized cross validation for wavelet thresholding
Signal Processing
A Theoretical Tour of Connectivity in Image Processing and Analysis
Journal of Mathematical Imaging and Vision
A new fuzzy connectivity class application to structural recognition in images
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Flat zones filtering, connected operators, and filters by reconstruction
IEEE Transactions on Image Processing
Fast fuzzy connected filter implementation using max-tree updates
Fuzzy Sets and Systems
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Fuzzy connected filters were recently introduced as an extension of connected filters within the fuzzy set framework. They rely on the representation of the image gray levels by fuzzy quantities, which are suitable to represent imprecision usually contained in images. No robust construction method of these fuzzy images has been introduced so far. In this paper we propose a generic method to fuzzify a crisp image in order to explicitly take imprecision on grey levels into account. This method is based on the conversion of statistical noise present in an image, which cannot be directly represented by fuzzy sets, into a denoising imprecision. The detectability of constant gray level structures in these fuzzy images is also discussed.