We have developed a method based on wavelets to obtain the true underlying smooth density from a point distribution. The goal has been to reconstruct the density field in an optimal way, ensuring that the morphology of the reconstructed field reflects the true underlying morphology of the point field, which, as the galaxy distribution, has a genuinely multiscale structure, with near-singular behavior on sheets, filaments, and hot spots. If the discrete distributions are smoothed using Gaussian filters, the morphological properties tend to be closer to those expected for a Gaussian field. The use of wavelet denoising provides us with a unique and more accurate morphological description.