Denoising diffusion model as handwritten digit generator

Abstract

The diffusion model is the process by which variables are introduced and propagated through a population. The equation can be applied to any physical system that exhibits such processes through time. Generally speaking, diffusion occurs when a physical system is connected to another by a small number of interconnected points; the interconnected points' overall connectivity can be represented by a network. The diffusion model is a mathematically defined process used to analyse the movement of particles from a region of high concentration to that of low concentration. Based on the diffusion coefficient and polarization, several studies have established that the equilibrium port-to-port distance can be calculated. The diffusion model is useful for solving the problem of noise in imaging systems, especially when an object has similar properties in all directions. When discussing diffusion, it is essential to refer to the diffusion coefficient. The literatures find denoising diffusion model to involves the process where a pixel value is estimated based on values at surrounding pixels. On the other hand, a forward process is passing through an image and replacing pixels based on their quality estimates. Reconstruction involves reconstructing an image from its components, including the subsamples and low-quality components. This model achieves satisfactory performance on digital number image generation.