Investigating the defects of gas pipes with industrial gamma radiography method and weighted anisotropic–isotropic total variation

Industrial gamma radiography is used to test the defect of thick pipes in the oil and gas industry. Due to the high energy of the gamma sources used in radiography, the permeability is high in parts with a thickness of several inches and gives a good image of the internal characteristics of the pipe. Due to various factors such as the scattering of gamma rays and the stages of emergence and proofing of the film, the recorded image is usually blurred. The resolution and contrast of radiographic images have an important rule for precise interpretation and better defect detection. Different methods of image processing, both in the frequency and spatial domains, can be useful for improving the quality of radiographs. Various types of total variation-based methods have been used to improve the quality of images in different types of image processing problems. In this research, the weighted isotropic-anisotropic total variation method (WAITV) has been used to process and improve the contrast of radiographic images. This method works on the basis of horizontal and vertical differential operators and isotropic and anisotropic conversion functions and provides fast algorithmic coefficients for optimization using the alternating path method. This algorithm was applied to 24 prepared radiographic images and the original and processed images were evaluated by experts. The results of the evaluation show that, according to specialists, the use of the WAITV method has an effect of 10 to 20% in improving the contrast of radiographic images. In general, the edges of the images are sharper and different regions such as IQI lines and defects are better seen in the processed images. Experts also emphasize that due to the changes in brightness in the pixels and the possibility of creating false defects, the use of this method and other processing methods can only be interpreted when compared with the original radiographic image.