Abstract

We have presented in this paper a new enhancement technique utilizing the high-frequency component information and the edge information sensor defined in Ramponi's method. These kinds of information were used in Ramponi's method, and it is clear that they were effective for the enhancement of noisy images, carrying out enhancement of edges only without enhancing the noise. However, enough extraction is not done because of the way the two kinds of information are considered. Therefore, we proposed in this paper a method based on fuzzy inference, in which the antecedent variables are these two kinds of information and the inference result is the enhancing component. The fuzzy sets for both kinds of information were established experimentally. Through application examples we made clear that we can set the fuzzy sets independently of the kind of images or the additive noise variance, and still greatly improve the enhancement results from Ramponi's method. In this paper we focused on the tuning of the enhancement function ƒ(i,j), whose variables are the edge information sensor defined by Ramponi (square of amplitudes) and the high-frequency component information. Naturally, the scheme of computation for the edge information sensor is still one subject of study, but we leave this topic for further investigation. © 2000 Scripta Technica, Electron Comm Jpn Pt 3, 83(7): 1–11, 2000

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