Study On Adaptive Enhancement Algorithm For X-ray Image Of Complex Abnormity Workpiece

X-ray testing has been widely used in the field of nondestructive testing because of its advantages such as no damage to the tested objects and intuitive display of defect images.However,in the detection process of complex special-shaped structural parts with complex shape,structure and material diversity,due to the complex structure of the complex special-shaped workpiece and the characteristics of X-ray imaging,the obtained digital X-ray image contrast is low,thus affecting the effective detection of workpiece quality.Therefore,it is urgent to propose an effective image enhancement method to improve the quality of low-contrast radiographic images of special-shaped workpiece with complex structure.Based on partial differential equation for the problem of minimizing the energy functional of the relevant theoretical knowledge,carried out the complex adaptive enhancement special-shaped workpiece algorithm research,implements for complex shaped workpieces ray image brightness,contrast adaptive to ascend,the enhanced image can satisfy the detection requirements of subsequent complex shaped workpiece.To solve the above problems,this paper proposes an adaptive enhancement algorithm based on image local variance and variational method.Firstly,the algorithm extracts the contrast information of the image based on the gradient field of the image,and then constructs the image contrast enhancement model based on the contrast field.Then,the local variance of the image was calculated,and the image contrast enhancement model was improved by using the adaptive gain function of the local variance of the image,and the non-local mean filtering was used to suppress the noise of the gradient field after optimization.Finally,the minimum functional equation between the promoted gradient field and the target image is established based on the relevant theoretical knowledge of partial differential equation,and the equation is solved by the variational method,and the target image is finally obtained.But considering the local variance of the image only can describe the image of the local information of fluctuations,are greatly influenced by noise,so this article embarks from the image itself gradient information,design the structure tensor based on adaptive enhancement and variational method algorithm,this algorithm by using the properties of the eigenvalues of the image structure tensor design adaptive gain function to improve the image contrast enhance model.Finally,in order to verify the effectiveness of the proposed algorithm,the experimental results are evaluated from both subjective and objective aspects in combination with commonly used image quality evaluation parameters.The results show that the proposed method can effectively enhance X-ray images and has excellent performance in detail protection and noise suppression.