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Improved Bi-optimal Hybrid Approximation Algorithm for Monochrome Multitone Image Processing

Authors:
Rudolf Neydorf
Albert Aghajanyan
Dean Vucinic

Keywords: heuristic algorithms; evolutionarily-genetic algorithm; image approximation; optimization; hybridization; bi-optimization

Abstract:
The paper investigates image tones approximation algorithm for the multitone image processing, which applications examples are in Web development, compression algorithms, machine vision etc. It considers the Monochrome Multitone Image (MMI) approximation of the original palette to be replaced by a palette having significantly less number of tones. For solving such problems, the optimization strategy requires the approximation quality, which maximizes the tones reduction deviation between the original and the approximated images. In particular, such problems are effectively solved with the heuristic Evolutionarily Genetic Algorithms (EGA) fulfilling the required accuracy, while computational costs still remain significant. Thus, this research is focusing on the hybrid algorithm that is combining the heuristic algorithm, in order to provide suboptimal approximation quality, and the deterministic Algorithm of Local Discrete Optimization (ALDO) for finding the local extreme. EGA minimizes the local discrete optimization search area and ALDO guarantees to find the extreme within the search area. In conclusion, such hybrid algorithmic architecture enables the MMI bi-optimization approximation.

Pages: 20 to 25

Copyright: Copyright (c) IARIA, 2017

Publication date: November 12, 2017

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-599-9

Location: Barcelona, Spain

Dates: from November 12, 2017 to November 16, 2017