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Color image reduction by minimizing penalty functions
conference contribution
posted on 2012-01-01, 00:00 authored by D Paternain, A Jurio, Gleb BeliakovGleb BeliakovIn image processing, particularly in image reduction, averaging aggregation functions play an important role. In this work we study the aggregation of color values (RGB) and we present an image reduction algorithm for RGB color images. For this purpose, we define and study aggregation functions and penalty functions in product lattices. We show how the arithmetic mean and the median can be obtained by minimizing specific penalty functions. Moreover, we study other penalty functions and we show that, in general, aggregation functions on product lattices do not coincide with the cartesian product of the corresponding aggregation functions. Finally, we make an experimental study where we test our reduction algorithm and we analyze the stability of the penalty functions in images affected by noise.
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Event
IEEE International Conference on Fuzzy Systems (2012 : Brisbane, Queensland)Pagination
205 - 211Publisher
IEEELocation
Brisbane, QueenslandPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2012-06-10End date
2012-06-15ISBN-13
9781467315050Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2012, IEEETitle of proceedings
WCCI 2012 : Proceedings of the IEEE World Congress on Computational IntelligenceUsage metrics
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