Evaluating Blind Image Quality Using RBF Neural Network

Authors

  • Abi Soliga Sathyabama University
  • Godlin Jasil Sathyabama University

DOI:

https://doi.org/10.34306/csit.v1i1.40

Keywords:

Blind image quality assessment, Radial bias function (RBF) neural network, Multivariate Gaussian

Abstract

Blind Image Quality Assessment (BIQA) methods are the most part feeling mindful. The BIQA method learns regression models from preparing images with human subjective scores to predict the perceptual nature of test images. The general quality of image and the nature of every image patches are measured by normal pooling. By coordinating the components of normal picture measurements got from different signs, we take a multivariate Gaussian model of picture patches from an accumulation of unblemished regular pictures. The proposed radial bias function neural network method is used to evaluate the quality of images and this method represents the structure of picture distortions with flexibility.

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References

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Published

2016-02-25

How to Cite

Soliga, A., & Jasil, G. (2016). Evaluating Blind Image Quality Using RBF Neural Network. APTIKOM Journal on Computer Science and Information Technologies, 1(1), 23–26. https://doi.org/10.34306/csit.v1i1.40

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Section

Articles