The Application Study Of PPB Weighted Maximum Likelihood Estimationand And Variance Stabilizing Transformation On Neutron Image Denoising

Neutron radiography technology is an important nondestructive testing technology,which uses the image of neutron penetrating material to display the internal details and structure information of an object.In view of neutron's unique properties,neutron radiography technology has the irreplaceable function compared with traditional nondestructive testing,especially to detect internal light elements of thicker metal casing like hydrogen,lithium,etc.Neutron imaging will be affected by noise pollution caused by various factors.It mainly includes the quantum properties and randomness of neutron beam,CCD camera influenced by environment,the gamma ray pollution and the dark current noise.The statistical characteristics of these noises are similar to mixture distribution of Poisson and Gaussian,which seriously affects neutron image quality and the accuracy of neutron radiography technique in nondestructive testing.Therefore,it is very important to research neutron image denoising.In order to remove the mixed noises in neutron image,in this paper,we introduce the Anscombe nonlinear variance stabilizing transformation into PPB weighted maximum likelihood estimation for denoising.Firstly,transforming the image data through Anscombe nonlinear variance stabilizing transformation,the mixed noises submitted to Poisson-Gaussian distribution are transformed into a single noise obeyed Gaussian distribution.Through this transformation,it reduces the difficulty of removing Poisson noise in neutron image.Secondly,PPB weighted maximum likelihood estimation is used to filter the transformed image,which not only is able to remove the Gaussian noise effectively,but also overcome artifacts in existing denoising algorithms,It is helpful to improve neutron image quality and increase the accuracy of neutron radiography in nondestructive testing.Finally,the data is restored by the Anscombe unbiased inverse transform to obtain the restored neutron image.The peak signal to noise ratio(PSNR)is used to evaluate denoising results in simulated image,with the real neutron image,further to verify the denoising method which combining the Anscombe nonlinear variance stabilizing transformation with PPB weighted maximum likelihood estimation that it is effective to remove mixed noise of Poisson and Gaussian in neutron image.