Recently, radiography image elaboration using different image processing methods has been introduced as an alternative to enhance the radiographs. The ability of improving the quality of an image depends on the scattered x-ray and the acquisition data by electronic system in digital radiography (DR) (RT). Iterative methods, well known in general sparse signal reconstruction, can be suited for the radiography images. In this research, the DR image is improved by minimizing an objective function using the fast iterative shrinkage-thresholding algorithm (FISTA), Monotone FISTA (MFISTA), over relaxation MFISTA (OMFISTA) and converged FISTA, where the solution sparsity may be adjusted as desired. The paper surveys four well-known methods for sparse process, and assesses their optimization parameters with the goal of obtaining the best algorithm for industrial radiography images. First, the radiographs from the welded objects were provided and four iterative methods were implemented to the radiographs for enhancing the contrast. Then reconstructed images were assessed on the basis of their quality. The results show that the reconstructed images have better contrast than the original radiography and the OMFISTA method has a lower runtime compared to others. Also, the results demonstrate the viability and efficiency of the four proposed algorithms on radiography image deblurring problems without any information about the noise of radiography system.
Read full abstract