A Nonlinear Diffusion Model with Smoothed Background Estimation to Enhance Degraded Images for Defect Detection

It is important to detect the defect of products efficiently in modern industrial manufacturing. Image processing is one of common techniques to achieve defect detection successfully. To process images degraded by noise and lower contrast effects in some scenes, this paper presents a new energy functional with background fitting, then deduces a novel model which approximates to estimate the smoothed background and performs the nonlinear diffusion on the residual image. Noise removal and background correction can be both successfully achieved while the defect feature is preserved. Finally, the proposed method and some other comparative methods are performed on several experiments with some classical degraded images. The numerical results and quantitative evaluation show the efficiency and advantages of the proposed method.