Evaluation Error Measurement Tools Based on Blurred Image

Authors

  • Farah Sari Computer science Department, Kufa University, Iraq

Keywords:

Degraded colored image, Mean filters, Error measurement tools and Statistics analysis.

Abstract

There are many paper used difference type of quality measurements without evaluate them to find the best one, in this paper create new comparative study between various type of error measurements tools. This comparison rely on characteristics of that error tools, where everyone have set of advantage and drawbacks, in addition where it can use exactly and what is the accuracy of result which can be provided. Overall this research focused on blurred images after manipulate it using more than one mean filters with set of image sample. So then mean reason for this research make best decision to select strong tools among different type of tools. Finally make over view to use the correct tool with specific purpose.

References

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Mahdi Shaneh et al, Image Enhancement using ?-Trimmed Mean ?-Filters, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, Vol 5, pp. 11, 2011.

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H. R. Wu et al, Digital Video Image Quality and Perceptual Coding, Nov. 2005.

Ravi Kumar, Munish Rattan, Analysis Of Various Quality Metrics for Medical Image processing, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 11, November 2012.

Cort J. Willmott, Kenji Matsuura, Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance, Center for Climatic Research, Department of Geography, University of Delaware. Vol. 30, pp. 79

Jan Kotera et al, PSF Accuracy Measure for Evaluation of Blur Estimation Algorithms, GACR, 2015.

T. Chai, R. R. Draxler, Root mean square error (RMSE) or mean absolute error (MAE) Arguments against avoiding RMSE in the literature, Geosci, 30 June 2014.

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Published

2016-12-14

How to Cite

Sari, F. (2016). Evaluation Error Measurement Tools Based on Blurred Image. International Journal of Sciences: Basic and Applied Research (IJSBAR), 30(5), 130–139. Retrieved from https://www.gssrr.org/index.php/JournalOfBasicAndApplied/article/view/6660

Issue

Vol. 30 No. 5 (2016)

Section

Articles

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