2 January 1998 Estimation of error diffusion kernel using genetic algorithm
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Error diffusion technique has been one of the most popular digital image halftoning methods. The quality of binary image resulting from the error diffusion technique is affected by the following three key factors; the values of error diffusion kernel, the locations of neighboring pixels for error propagation, and the quantization scheme. Among these factors, this paper is focused on the estimation of the values of error diffusion kernel. In previous efforts to propose modification to the original Floyd-Steinberg's algorithm, the values of error diffusion kernel have been determined by the trial and error method or by utilizing optimization techniques such as the least mean square estimation and neural network methods. This paper presents a new estimation method for the values of error diffusion kernel based on the genetic algorithm. Compared to the conventional optimization techniques, the genetic algorithm based approach lifts restrictions on the complexity of the error criterion for optimization. In this paper, two types of the error criteria are defined to improve image quality. They represent a measure of the reproduction of average brightness and an extent of undesirable artifacts appeared on the binary image for specific gray levels. The values of error diffusion kernel are estimated by simultaneously minimizing the defined error criteria using genetic algorithm. In the experiments, three types of error diffusion kernel are examined. The experimental results indicate that the binary images obtained based on the estimated error diffusion kernel exhibit less artifacts.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Seung-Ho Park, Seung-Ho Park, Ki-Min Kang, Ki-Min Kang, Choon-Woo Kim, Choon-Woo Kim, } "Estimation of error diffusion kernel using genetic algorithm", Proc. SPIE 3300, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts III, (2 January 1998); doi: 10.1117/12.298296; https://doi.org/10.1117/12.298296


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