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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

The SNCD as a Metrics for Image Quality Assessment

Author 1: Avid Roman-Gonzalez
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 4, No. 7 · Published 2013

DOI: https://doi.org/10.14569/IJACSA.2013.040706

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Abstract

In our era, when we have a lot of instrument to capture digital images and they go more in more increasing the image resolution; the quality of the images become very important for different application, and the development tool to quality assessment is a current issue. In this paper, we propose to use the Symmetric Normalized Compression Distance (SNCD) as a metrics for the measurement of image quality, especially when we analyze residual errors. We also show performance comparisons of other metrics that we can found in the various research literatures and the SNCD. We also present an analysis about the performance of the SNCD depending to the type of distortion.

Keywords

Quality metrics NCD SNCD Kolmogorov complexity image quality.

How to Cite this Article

Roman-Gonzalez, A. (2013). The SNCD as a Metrics for Image Quality Assessment. International Journal of Advanced Computer Science and Applications, 4(7). https://doi.org/10.14569/IJACSA.2013.040706

Roman-Gonzalez, Avid. "The SNCD as a Metrics for Image Quality Assessment." International Journal of Advanced Computer Science and Applications, vol. 4, no. 7, 2013, https://doi.org/10.14569/IJACSA.2013.040706.

@article{Roman-Gonzalez2013,
  title     = {The SNCD as a Metrics for Image Quality Assessment},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {4},
  number    = {7},
  year      = {2013},
  publisher = {The Science and Information Organization},
  author    = {Avid Roman-Gonzalez},
  doi       = {10.14569/IJACSA.2013.040706},
  url       = {https://doi.org/10.14569/IJACSA.2013.040706}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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