- Fitting a Surface: You can fit a mathematical surface to your data points using functions like “fit” from the “Curve Fitting Toolbox”. This could involve fitting a “spline” or other smooth surface to your data. You can then evaluate the surface at a grid of points to plot it.
- Using MATLAB's “griddata” or “scatteredInterpolant”: These functions can interpolate the surface at points on a grid based on the scattered data points
- Using a Smoothing Algorithm like Laplacian Smoothing or HC-Smoothing: There are mesh smoothing algorithms like Laplacian smoothing and HC (Humphrey’s Classes) smoothing that can be applied to the vertices of a triangulated mesh to make the surface appear smoother.
- Using MATLAB's “smooth3” function: If you have a volumetric data, you can use this function to smoothen it.
- fit: https://www.mathworks.com/help/curvefit/fit.html?searchHighlight=fit&s_tid=srchtitle_support_results_1_fit
- Smoothing Splines: https://www.mathworks.com/help/curvefit/smoothing-splines.html?searchHighlight=spline&s_tid=srchtitle_support_results_4_spline
- griddata: https://www.mathworks.com/help/matlab/ref/griddata.html?searchHighlight=griddata&s_tid=srchtitle_support_results_1_griddata
- scatteredInterpolant: https://www.mathworks.com/help/matlab/ref/scatteredinterpolant.html?searchHighlight=scatteredInterpolant&s_tid=srchtitle_support_results_1_scatteredInterpolant
- smooth3: https://www.mathworks.com/help/matlab/ref/smooth3.html?searchHighlight=smooth3&s_tid=srchtitle_support_results_1_smooth3