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Industrial radiography is considered as one of the most important nondestructive testing methods for different inspections. The radiography images often have a poor signal-to-noise ratio mainly because of the scattered X-rays. Image processing methods may be used to enhance the contrast of radiographs for better defect detection. In this study, outcomes from three total variations (TV) based methods were analyzed and compared. Implemented algorithms were ROF-TV, non-convex p-norm total variation (NCP-TV) and non-convex logarithm-based total variation (NCLog-TV). These TV-based methods have been implemented indirectly as high pass edge-enhancing filters. Based on qualitative operator perception results, the study has shown that the application of all three methods resulted in improved image contrast enabling enhanced image detail visualization. Subtle performance differences between the outputs from different algorithms were noted, however, especially around the edges of image features. Furthermore, it was found that all implemented algorithms have similarities in performance, generate approximately the same results and are suitable for weld inspection. [ABSTRACT FROM AUTHOR]

The life of an aircraft depends on the early detection and removal of corrosion in its structure. The importance of detecting corrosion cannot be understated, because corrosion can cause other kinds of damage, such as cracks. Radiography is an important method for the detection of hidden defects in aircraft structure. To maximize information extraction from the radiographic images, the noise of the system should be minimized, or the contrast of the defective region should be maximized by different methods. The development of effective image processing methods, within both the spatial and frequency domains, is important to the research of industrial radiographic testing. In this study, the geometric locally adaptive sharpening method was used to improve hidden structure visualization of details and defects from aircraft part radiographs. The method relies on sharpening by using the steering kernel regression method. Here, the enhancing contrast and sharpening algorithm are effectively mixed together. The proposed algorithm was successfully applied to radiographic images of aircraft parts. An improvement of the structure detail visualization and defect region detection was achieved by sharpening the edges and preserving fine detail imaging information. Experts' reviews showed that defect regions from the geometric locally adaptive sharpening reconstructed images were better visualized than the original images. Also, the resulting evaluation of the output images shows that the edges are sharpened by the proposed method and that the background of the image decreases to zero. [ABSTRACT FROM AUTHOR]

Testing and detecting potential defects in works of art is usually required to cause minimal or no damage; industrial Radiography Testing (RT) is often the method of choice provided the images are of the required high quality and yield high defect detection sensitivity. Various digital image processing methods can be employed to achieve improved image quality and information extraction as required. The level and nature of the noise in the RT images is usually unknown. In addition to the different noises, the image quality is degraded by the blurring effect. In this study, a modified form of the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) with quadratic regularization strategy was developed and applied to remove the blurring. The output of the application of the method to number RT images of five art objects was evaluated by industrial radiography and antiquities experts. It was confirmed that the applied method was efficient and improved image quality and defect detection. [ABSTRACT FROM AUTHOR]

Availability of pertinent and detailed information for damaged ancient objects is vital for successful restorative, damage limitation intervention processes in archeology. Visual inspection and radiography testing (RT) constitute widely used non-destructive methods for conservators of such objects. Unfortunately, the quality of RT images is susceptible to blurring caused by the superimposed scattered X-rays. In this study, the no-black-pixel constraint (NBPC) algorithm on its own as well as in the form of an algorithm with the planar-scene assumption (NBPC + PA) was applied to RT images with a view to suppressing image blurring and enhancement of imaging contrast. The results of this study have shown, both qualitatively and quantitatively that the NBPC + PA and NBPC algorithms provide higher imaging contrast for identification and evaluation of damage in corroded ancient metallic relics than using unprocessed RT images alone. Contrast enhancement of up to about 120% and 78% was achieved in comparison with the original image by applying the NBPC+PA and NBPC algorithms, respectively. Practical application and effectiveness of using the processed images were evaluated by expert operators in the area and it was found that using the reconstructed images scored higher (on average by 88%) than the original RT images (on average by 73%) with the NBPC+PA scoring higher (on average by 91%) than the NBPC algorithm (on average by 85%). The operators have found utilizing the processed images leads to better inspection and evaluation of the object enabling better targeted informed for restorative intervention, damage limitation, and maintenance of such objects. [ABSTRACT FROM AUTHOR]

This study improves the performance of primal-dual interior-point method in inverse conductivity problems via replacing the conventional, complicatedly calculated scalar regularization parameter with a diagonal matrix termed "multi-regularization parameter matrix" here. The solution of the PD-IPM depends considerably on the choice of the regularization parameter. Calculation of the optimal regularization parameter, which yields the most accurate solution, is not simple due to the long iterative nature of the algorithm. The objective optimization, which is implemented by minimizing error in the solutions over an extensive range of the regularization parameters, yields the most accurate solution that can be achieved, although this method is not applicable in reality due to lack of knowledge about the actual conductivity field. However, the modified algorithm not only solves the problem independently using the regularization parameter, but also increases the accuracy of the solution, as well as its sharpness in comparison to the objective optimization. [ABSTRACT FROM AUTHOR]

The most technically available NDT method for in-service inspection of heat exchanger tubes is eddy current testing. Using a differential ID bobbin probe, tubes can be tested with high speed, but for accurate estimation of tube condition, precisely machined calibration blocks from the same material are necessary. The purpose of this work was to calibrate the eddy current system by radiography without the use of expensive calibration blocks. Wall thickness measurement and deterioration determination due to corrosion/erosion/pitting was evaluated in this study by using radiograph ie film density measurements. It was found that this method can determine the remaining wall thickness as well as pitting corrosion in the tubes using differential and absolute film density measurements. Results show that good precision can be obtained with this method of eddy current system calibration. [ABSTRACT FROM AUTHOR]