FISTA Algorithm for Radiography Images Enhancement with Background Blurring Removal
Effat Yahaghi, Mahdi Mirzapour, Amir Movafeghi, Parisa Mohammadi Matin, Behrouz Rokrok · Research in Nondestructive Evaluation · 2018
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.