A novel algorithm of PCNN-based point set surface denoising is proposed in this paper.The algorithm mainly includes two steps:location of noise points and smoothing of the located noise points.Firstly

a pulse-coupled neural network for the point set surface is constructed.The stimulation value of each neuron is decided by the differences of the position and the normal of the k-nearest neighbor points.The noise points are located through the adaptive firing capture feature of the PCNN.Based on the idea of bilateral filtering

the located noise points are smoothed

while the non-noise points remain their geometry position.Due to the different operations on noise points and non-noise points

experiments show that our algorithm performs better to remove the noise of the point set surface while keeping the features of the model.