By analyzing the patterns underlying these irregular noise distributions, we turn to mathematical models such as random walks or random-phase sums, which govern noise behavior.
A typical signal can be expressed as sinusoidal functions of time and space, enabling noise to be transformed into controllable 3D data. Leveraging this approach, I begin exploring ways to reshape the surface and morphology of 3D models.