Application of adaptive contrast enhancement algorithm based on particle swarm optimization in neutron radiography

Abstract

BackgroundDue to the imaging mechanism of neutron radiography and the limitation of neutron source, neutron radiography images are prone to lack of contrast, and it is a common method to improve image quality by contrast enhancement algorithm.PurposeThis study aims to solve the problems related to low contrast and loss of details in neutron imaging.MethodsAn adaptive contrast enhancement (ACE) algorithm based on the particle swarm optimization (PSO) was proposed. First of all, the gain factor coefficient was treated as a particle and initializes a particle swarm. Then, the optimal gain factor coefficient with the PSO algorithm was calculated, and the contrast of the high frequency part of neutron images was improved through implementing this optimal gain factor coefficient in ACE algorithm. Finally, several neutron images were processed by this PSO algorithm and compared with the results of traditional optimization algorithm.ResultsThe new algorithm has obvious contrast enhancement effect for different neutron images, and the parameters such as entropy value, gray average gradient value and contrast value of the optimized image are improved compared with the traditional optimization algorithm.ConclusionsThis algorithm can enhance the contrast of image stably, which has practical significance for the wide application of neutron radiography.

Keywords

• neutron radiography
• image enhancement algorithm
• adaptive contrast enhancement
• particle swarm optimization