An novel image de-noising model based on gradient and adaptive curvature features and its application

Abstract

In this paper, an image de-noising model with gradient and adaptive curvature features is proposed for the visual inspection of the appearance defects of high-density flexible integrated circuit package substrates with strict line-width and line distance. Firstly, the model proposed in this paper adaptively adjusts the weight of the level set curvature feature and the gradient feature of the image, and uses more abundant first-order differential and second-order differential information of the image as the detection factor for image de-noising. Secondly, theoretical analysis shows that the diffusion intensity of the model in the flat region is larger than that of the classical model, and the de-noising effect is better. Furthermore, at the corners and peaks of the image, the proposed model can suppress the reduction of the gray value and preserve more detailed information of the image and edges. Finally, the experimental analysis shows that the proposed model has the best de-noising effect compared with other models. The method proposed in this paper can effectively remove the noise of the image of the high-density flexible integrated circuit package substrate, and at the same time retain more original details and edge information of the image which has practical significance.