In group decision-making situations, the decision-makers' opinions are generally characterized by subjectivity, imprecision and vagueness. Such opinions can be represented by fuzzy numbers such as positive trapezoidal fuzzy numbers. Several aggregation methods have been proposed previously; however, there are still deficits which limit their applications. This paper proposes an aggregation method based on centroid measurement which aims to overcome some of the shortcomings. In the paper, a number of axioms are proposed. A numerical example is given at the end to illustrate the application of the proposed aggregation method.
Preserving meaningful details such as blurred thin edges and low-contrast fine features is important in image de noising. A new method based on improved anisotropic diffusion model and wavelet transform is presented for image denoising. The proposed diffusion model incorporates both local gradient and gray-level variance to preserve edges and fine details while effectively removing noise in low-contrast surface images.
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