A new SVTV-Stokes model with Bayesian optimization for color image denoising
Yitao Sheng, Zhigang Jia · Inverse Problems and Imaging · 2025
A new model is proposed for color image denoising, with combining tangential field smoothing techniques, image reconstruction techniques, and Bayesian optimization methods. First, the smooth tangential vector field method is used to process the color image, and the 'texture' information of the denoised image is obtained by using the anisotropic TV-Stokes model to effectively improve the smoothness of the image. Second, owing to the regularization characteristics of the SVTV model, the image is further refined after premilinary processing, with colors smoothed and details preserved. This process helps eliminate noise to the maximum extent while maintaining the natural appearance of the image. Bayesian optimization methods are then used to optimize the parameters to improve the algorithm's performance. Numerical experimental results demonstrate that the proposed method can effectively capture details in color images, exhibiting superior denoising effects. The new model proposed in this paper brings innovation and effective solutions to the field of color image denoising, offering important insights and guidance for research and applications in image processing. This model is expected to provide reliable technical support for enhancing image quality and information extraction in practical applications.