3-D geometric signal compression method based on compressed sensing

This paper provides a compression method of three-dimensional meshes based on compressed sensing. First, this method gets the 3-D geometric signal through discrete representing the three-dimensional meshes. Then, we construct a basis using Laplace operator of the three-dimensional meshes. Thus, we get the sparse representation of the 3-D geometric signal based on this basis. Last, we complete compressing the three-dimensional meshes, through random sampling geometry signals based on compressed sensing. In the recovery process, we reconstruct the 3-D geometric signal through optimizing 1-norm of the sparse signal. This method completed the compression of three-dimensional meshes in the sampling process. Experimental results show that the compression ratio of this method is high, the restore effect is good and it is suitable for large-scale data compression.