Research Of Neutron Image Restoration Algorithm Based On Regularization

As a non-destructive testing technology, neutron imaging a growing concern. Due to limitations of the imaging system, resulting in poor image quality neutron image. Image restoration, is to remove or alleviate the decline in the quality of the target image, it tends to be restored as an ideal image is not degraded. So the study of image restoration technology not only has important theoretical significance, but also in real life applications, there is an urgent need. This article dedicated to the research neutron image restoration technology to improve image quality, making it more a reflection of the internal structure of the object.Based on the regularization method to solve the blind image restoration technology in the ill-posed problem, analysis and comparison of the Laplace?Laplacian? regularization and total variation?TV? regularization algorithm advantages and disadvantages, the total variation regularization algorithm based on the use of adaptive thresholds joint variational regularization blind image restoration, neutron image restoration. The restoration algorithm into a joint variational regularization term, using the L₁ norm is more suitable image space,removing image noise while maintaining a better image edge and texture information.Finally, the solution process, the introduction of an auxiliary variable transformed model solution to avoid the accumulated error variable approximate bring improve the recovery accuracy. By comparing the experimental results demonstrate that the algorithm effectively improve the quality of the neutron image.