关键词: 图像去噪, 变分法, 偏微分方程, 混合去噪模型, 数值仿真

Abstract: Image denoising is an important branch in the field of digital image processing. The purpose is to remove the noise while maintaining the useful information such as contrast, clarity and texture of the image. It is the premise of image segmentation, feature extraction and target recognition and other image processing process. In order to effectively suppress the impulse noise and overcome the shortages of the harmonic model and the TV-[L1] model, a hybrid variational model with fidelity items for impulsive noise denoising is proposed. The numerical algorithm is realized by the augmented Lagrangian algorithm. The de-noising effect of the image is evaluated by peak signal-to-noise ratio, root mean square error. The experimental results show that the model has higher peak signal to noise ratio than other types of existing models, effectively reducing the root mean square error, and CPU time is shorter. This model has better denoising performance, a better visual effect is obtained. Not only the image quality is improved, but also the effectiveness is confirmed objectively.