Improvement and comparison of X and Neutron radiography images by Gaussian Convolution Method

Abstract

X-rays and neutron radiography images are one of the most effective defects and structure detection methods. The interactions between neutrons and X-rays are different in the material, and therefore, different information can be obtained from the radiographs. Due to neutron and X-rays photon scattering, focal spot size, electronic noises, etc., the images are blurred and their quality is reduced. In this study, while investigating the radiographs of X-rays, and neutrons, the defects and internal structure of objects are investigated. The results show that neutron radiography performs very well in detecting the internal structure of low atomic number materials. X-ray radiography is effective for high atomic numbers as metal. Gaussian convolution is used to enhance the radiography images and reduce blurriness components. The results show that by reducing the background, the blurriness components can be reduced and the defects areas and internal structure of the objects can be better investigated. Specialists evaluated the results in radiography; the results show that the expert’s evaluation approved the image enhancement.

Keywords

• x-rays radiography
• neutron radiography
• structure defects
• image processing
• gaussian convolution