Sinha-Dougherty approach to the fuzzification of set inclusion revisited
Fuzzy Sets and Systems - Implication operators
Image and Vision Computing
Fuzzy techniques in image processing at Ghent University
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Dedicated to the 60th birthday of Etienne E. Kerre
Gaussian noise reduction in greyscale images
International Journal of Intelligent Systems Technologies and Applications
The possibilities of fuzzy logic in image processing
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Image similarity: from fuzzy sets to color image applications
VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
Efficient video breakup detection and verification
Proceedings of the 3rd international workshop on Automated information extraction in media production
Evaluation of the perceptual performance of fuzzy image quality measures
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
WILF'03 Proceedings of the 5th international conference on Fuzzy Logic and Applications
A novel histogram based fuzzy impulse noise restoration method for colour images
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
A new fuzzy multi-channel filter for the reduction of impulse noise
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
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Objective quality measures or measures of comparison are of great importance in the field of image processing. Such measures are needed for the evaluation and the comparison of different algorithms that are designed to solve a similar problem, and consequently they serve as a basis on which one algorithm is preferred above the other. Similarity measures, originally introduced to compare two fuzzy sets, can be applied in different ways to images. In [2] we gave an overview of similarity measures which can be applied straightforward to images. In this paper, we will show how some similarity measures can be applied to normalized histograms of images.