Open Access
ARTICLE
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
Cite This Article
M. B. Gharsallah, I. B. Mhammed and E. B. Braiek, "Improved geometric anisotropic diffusion filter for radiography image enhancement,"
Intelligent Automation & Soft Computing, vol. 24, no.2, pp. 231–240, 2018.