@Article{10798587.2016.1262457,
AUTHOR = {Mohamed Ben Gharsallah, Issam Ben Mhammed, Ezzedine Ben Braiek},
TITLE = {Improved Geometric Anisotropic Diffusion Filter for Radiography Image  Enhancement},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {2},
PAGES = {231--240},
URL = {http://www.techscience.com/iasc/v24n2/39749},
ISSN = {2326-005X},
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.},
DOI = {10.1080/10798587.2016.1262457}
}