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Improved Geometric Anisotropic Diffusion Filter for Radiography Image Enhancement


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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


Pages

Total Pages: 10
Pages: 231-240

DOI
10.1080/10798587.2016.1262457


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Published

Volume: 24
Issue: 2
Year: 2018

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References

Alvarez, Luis, Pierre-Louis Lions, and Jean-Michel Morel. "Image Selective Smoothing and Edge Detection by Nonlinear Diffusion. II." SIAM Journal on Numerical Analysis 29.3 (1992): 845-866. Crossref. Web. https://doi.org/10.1137/0729052

Ben Mhamed, Issam, Sabeur Abid, and Farhat Fnaiech. "Weld Defect Detection Using a Modified Anisotropic Diffusion Model." EURASIP Journal on Advances in Signal Processing 2012.1 (2012): n. pag. Crossref. Web. https://doi.org/10.1186/1687-6180-2012-46

Chao, Shin-Min, and Du-Ming Tsai. "An Anisotropic Diffusion-Based Defect Detection for Low-Contrast Glass Substrates." Image and Vision Computing 26.2 (2008): 187-200. Crossref. Web. https://doi.org/10.1016/j.imavis.2007.03.003

Liling, Ge, and Zhang Yingjie. "Weld Defect Detection in Industrial Radiography Based on Image Segmentation." Insight - Non-Destructive Testing and Condition Monitoring 53.5 (2011): 263-269. Crossref. Web. https://doi.org/10.1784/insi.2011.53.5.263

Guo, Jing-Ming et al. "Oriented Modulation for Watermarking in Direct Binary Search Halftone Images." IEEE Transactions on Image Processing 21.9 (2012): 4117-4127. Crossref. Web. https://doi.org/10.1109/TIP.2012.2198221

Michel-González, Eric, Min Cho, and Soo Lee. "Geometric Nonlinear Diffusion Filter and Its Application to X-Ray Imaging." BioMedical Engineering OnLine 10.1 (2011): 47. Crossref. Web. https://doi.org/10.1186/1475-925X-10-47

Mittal, Deepti et al. "Enhancement of the Ultrasound Images by Modified Anisotropic Diffusion Method." Medical & Biological Engineering & Computing 48.12 (2010): 1281-1291. Crossref. Web. https://doi.org/10.1007/s11517-010-0650-x

Perona, P., and J. Malik. "Scale-Space and Edge Detection Using Anisotropic Diffusion." IEEE Transactions on Pattern Analysis and Machine Intelligence 12.7 (1990): 629-639. Crossref. Web. https://doi.org/10.1109/34.56205

Ramos-Llorden, Gabriel et al. "Anisotropic Diffusion Filter With Memory Based on Speckle Statistics for Ultrasound Images." IEEE Transactions on Image Processing 24.1 (2015): 345-358. Crossref. Web. https://doi.org/10.1109/TIP.2014.2371244

Rudin, Leonid I., Stanley Osher, and Emad Fatemi. "Nonlinear Total Variation Based Noise Removal Algorithms." Physica D: Nonlinear Phenomena 60.1-4 (1992): 259-268. Crossref. Web. https://doi.org/10.1016/0167-2789(92)90242-F

Sauvola, J., and M. Pietikäinen. "Adaptive Document Image Binarization." Pattern Recognition 33.2 (2000): 225-236. Crossref. Web. https://doi.org/10.1016/S0031-3203(99)00055-2

Seddik, Hassene, Sondes Tebbini, and Ezzeddine Ben Braiek. "Smart Real Time Adaptive Gaussian Filter Supervised Neural Network for Efficient Gray Scale and RGB Image De-Noising." Intelligent Automation & Soft Computing 20.3 (2014): 347-364. Crossref. Web. https://doi.org/10.1080/10798587.2014.888242

Weickert, J., B.M.T.H. Romeny, and M.A. Viergever. "Efficient and Reliable Schemes for Nonlinear Diffusion Filtering." IEEE Transactions on Image Processing 7.3 (1998): 398-410. Crossref. Web. https://doi.org/10.1109/83.661190

Xu, Jiangtao et al. "An Improved Anisotropic Diffusion Filter with Semi-Adaptive Threshold for Edge Preservation." Signal Processing 119 (2016): 80-91. Crossref. Web. https://doi.org/10.1016/j.sigpro.2015.07.017

Yongjian Yu, and S.T. Acton. "Speckle Reducing Anisotropic Diffusion." IEEE Transactions on Image Processing 11.11 (2002): 1260-1270. Crossref. Web. https://doi.org/10.1109/TIP.2002.804276

Zahran, O. et al. "Automatic Weld Defect Identification from Radiographic Images." NDT & E International 57 (2013): 26-35. Crossref. Web. https://doi.org/10.1016/j.ndteint.2012.11.005

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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