A New Image Super-Resolution Reconstruction Algorithm Based on Hybrid Diffusion Model

Abstract

In the process of image denoising based on anisotropic diffusion model, the problem of edge information loss and “staircase effect” often appear. On the basis of anisotropic diffusion model, this paper combines the fractional diffusion model with the gradient based integer diffusion model, and introduces washout filter as the control term of the model, a new image super-resolution reconstruction algorithm based on hybrid diffusion model is proposed. In our proposed model, the fractional derivative will adjust its size adaptively according to the local variance of the image, and because the threshold k in the traditional diffusion function requires a lot of data experiments to get the best results, we also propose an adaptive threshold k function, whose value changes adaptively with the gradient of the image. Simulation results show that, compared with other algorithms, the new model still has a strong ability to retain image details and edge information after image reconstruction, and the introduced washout filter will also speed up the rapid convergence of the system to a stable state, and improve the convergence speed and stability of the system.