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Hybrid Optimization Method and Algorithms for Monochrome Images Tone Approximation with Implementation

The chapter considers the Monochrome Multi-tone Images (MMI) Tone Approximation (TA) problem. The TA procedure consists in reducing the image single-color tones palette size by replacing the original tones values with the approximated ones. The main problem is the selection of the appropriate approximation tones ; in other words, there is a need to define the optimal palette. To provide optimal TA for monochrome images a hybrid algorithm is developed and implies a 2- stage MMI processing. In the first stage the modified evolutionary-genetic algorithm is used. The main goal of the first stage is reducing the search area for the optimal approximation palette. In the second stage, the simple, but effective deterministic algorithm scans the nearest neighbourhood of the suboptimal solution, which was found in the first stage. The scanning of the nearest neighbourhood guarantees that the found extreme approximation palette is fulfilling the optimization criterion and that it is sub-optimized in respect to the total TA processing time.

Hybrid Optimization ; Monochrome Images ; Tone Approximation

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