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Improved Geometric Anisotropic Diffusion Filter for Radiography Image Enhancement

Mohamed Ben Gharsallaha, Issam Ben Mhammedb, Ezzedine Ben Braieka
a Research CEREP Unit, ENSIT, Tunis, Tunisia;
b Laboratory SIME, ENSIT, Tunis, Tunisia
* Corresponding Author: Mohamed Ben Gharsallah,

Intelligent Automation & Soft Computing 2018, 24(2), 231-240. https://doi.org/10.1080/10798587.2016.1262457

Abstract

In radiography imaging, contrast, sharpness and noise there are three fundamental factors that determine the image quality. Removing noise while preserving and sharpening image contours is a complicated task particularly for images with low contrast like radiography. This paper proposes a new anisotropic diffusion method for radiography image enhancement. The proposed method is based on the integration of geometric parameters derived from the local pixel intensity distribution in a nonlinear diffusion formulation that can concurrently perform the smoothing and the sharpening operations. The main novelty of the proposed anisotropic diffusion model is the ability to combine in one process noise reduction, edge preserving and sharpening. Experimental results using both synthetic and real welding radiography images prove the efficiency of the proposed method in comparison with other anisotropic diffusion methods.

Keywords

Radiography; welding; anisotropic diffusion; edge preserving; image sharpening; noise reduction

Cite This Article

. , "Improved geometric anisotropic diffusion filter for radiography image enhancement," Intelligent Automation & Soft Computing, vol. 24, no.2, pp. 231–240, 2018.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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