Assets evaluation credibility method based on the interpersonal relationship model

Cai, Lu; Zhai, Huiying; Liang, Yang; Tian, Xin

doi:10.1080/09720502.2017.1358881

Journal of Interdisciplinary Mathematics

2017

DOI: 10.1080/09720502.2017.1358881

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Assets evaluation credibility method based on the interpersonal relationship model

Lu Cai

Huiying Zhai

Yang Liang

et al.

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2019

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“…To a certain extent, the algorithm has achieved excellent restoration visual quality, but it takes a long time. And because the algorithm itself is too dependent on the similarity between the restored blocks and the sample blocks, the optimal matching for the restored block is not necessarily accurate [2,3,5,7,20]. Chandrasekaran et al proposed a linear addition function to the gradient and the logarithm of gradient to determine the restoration priority algorithm for the restored block.…”

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confidence: 99%

Research on iterative repair algorithm of Hyperchaotic image based on support vector machine

Li¹,

Cui²,

Sun³

et al. 2019

Discrete &Amp; Continuous Dynamical Systems - S

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The damaged area of the hyperchaotic image is prone to lack of texture information. It needs to make image restoration design to improve the information expression ability of the image. In this paper, an iterative restoration algorithm of hyperchaotic image based on support vector machine is proposed. The sample blocks in the damaged region of hyperchaotic images are divided into smooth mesh structures according to block segmentation method, and the neighborhood pixels of which points need to repair are ranked efficiently according to gradient values. According to the edge fuzzification features, the position of the important structural information of the damaged area is located. A multi-dimensional spectral peak search method is applied to construct the information feature subspace of image texture, so as to find the best matching block for restoring the damaged region of hyperchaotic image. Considering the features of structural information and texture information, the maximum likelihood algorithm is used to reconstruct the pixel elements in the image region by piecewise fitting. Through the support vector machine algorithm, the image iterative restoration is carried out. The simulation results show that the restoration method for hyperchaotic image can achieve effective restoration of image damaged area, the quality of restorationed image is better, and the computation speed is fast. The image restoration method can effectively ensure the visual effect of the reconstructed image. 2010 Mathematics Subject Classification. 46N30.

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confidence: 99%

Research on iterative repair algorithm of Hyperchaotic image based on support vector machine

Li¹,

Cui²,

Sun³

et al. 2019

Discrete &Amp; Continuous Dynamical Systems - S

View full text Add to dashboard Cite

show abstract

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Assets evaluation credibility method based on the interpersonal relationship model

Cited by 1 publication

References 6 publications

Research on iterative repair algorithm of Hyperchaotic image based on support vector machine

Research on iterative repair algorithm of Hyperchaotic image based on support vector machine

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