مشخصات پژوهش

عنوان	Enhancement of radiography images by two algorithms based on a cartoon–texture decomposition
نوع پژوهش	مقاله چاپ‌شده در مجلات علمی
کلیدواژه‌ها	industrial radiography, cartoon–texture image decomposition, nonlinear filter, total variation, defect detection
چکیده	Radiography is a technique used to view the internal defect regions in welded objects using x-rays or gamma rays. Information extraction from the radiographs depends on the image quality and the interpreter's skill. The use of image enhancement methods is an important goal in industrial radiographic testing for contrast improvement of radiographs. In this study, two cartoon–texture image decomposition methods (CTID) based on the nonlinear low pass and high pass filter (NLHF) algorithm and the total variation L1 (TV-L1) algorithm were used to detect and improve the defect(s) visualization in the radiographs of the GDXray database. These methods utilize iterative methods along with different filters to generate the cartoon and texture components of the image. The proposed methods were successfully implemented to the high and low contrast radiography images. Improvement in the defect regions was achieved while sharpening the edges and fine detail of the radiographs. Experts' evaluations showed that the contrast of the texture component in the NLHF method was better than the TV-L1 and the original radiograph.
پژوهشگران	پویان شایگان فرد (نفر اول)، عفت یاحقی (نفر دوم)، مهدی میرزاپور (نفر سوم)، امیر موافقی (نفر چهارم)