• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.183-193
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• 1998

Color inverse halftoning is the transformation of a color-halftone image to a continuous-tone color image that is more natural in human vision. In this paper, we propose a new smoothing mask that can remove halftone patterns in channel effectively and we apply it to color inverse halftoning. The proposed smoothing mask can make channel images more smooth and natural in human vision than traditional ones. Its characteristic can be adapted automatically according to the various color halftone images. We analyze the result images in various aspects through experiments. Experimental results show that the mask is useful for color inverse halftoning. It can be applied to field of multimedia application, such as desktop publishing, color facsimile and digital library construction.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.648-653
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• 2018

Analysis of a specific wavelength band of a video signal is an old research field. However, studies on the analysis of signals having the characteristics of a specific wavelength band or the generation of samples have been conducted actively in recent years. In this paper, we analyze the signal of digital halftoned image. The interpretation of halftoning in terms of signals was first made by Ulichney. We have come to the view that the signal characteristics between pixels used for half toning are good for blue noise. Lau has developed a halftoning method that uses green-noise characteristics by using output-dependent feedback as an error diffusion method. Jho has developed a method for producing halftoned images using a reaction diffusion model. In this paper, we analyze reaction diffusion halftoning in terms of signal to show green noise and compare it with existing green noise half tone.