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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 Beliakov
In 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.

History

Event

IEEE International Conference on Fuzzy Systems (2012 : Brisbane, Queensland)

Pagination

205 - 211

Publisher

IEEE

Location

Brisbane, Queensland

Place of publication

Piscataway, N.J.

Start date

2012-06-10

End date

2012-06-15

ISBN-13

9781467315050

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2012, IEEE

Title of proceedings

WCCI 2012 : Proceedings of the IEEE World Congress on Computational Intelligence