Binary genetic algorithm-based pattern LUT for grayscale digital half-toning

Abstract

Grayscale digital half-toning is a popular technique to reproduce grayscale images with devices that can support only two levels at output, i.e., black and white. Printers, LCD displays, etc. are some common examples of such devices. Considering 0 and 1 as black and white, respectively, this can be represented as an image-wise binary pattern generation process. The binary patterns are aimed to retain the local tonal and structural characteristics of grayscale image for a faithful illusion of the original grayscale image. Apart from tonal and structural characteristics retention, desired blue-noise characteristics also contribute significantly toward eye pleasant appearance of half-tone images. The paper presents a binary genetic algorithm-based approach to generate such binary patterns through optimizing randomly generated binary strings against a visual cost function. Paper also presents a pattern look-up-table (LUT)-based approach toward conventional clustered dot ordered dithering which is suitable for devices like laser or offset printers that cannot recognize individual pixels. The pattern LUT approach is driven toward green-noise characteristics instead of the blue-noise characteristics. The results obtained with test images are presented pictorially and evaluated through half-tone quality evaluation metrics. The evaluation results and comparison with state-of-art techniques shows the potential of presented technique for practical implementations.