We explore the filtering properties of wavelets functions in order to develop accurate and efficient numerical algorithms for Image Restoration problems. We propose a parallel implementation for MIMD distributed memory environments. The key insight of our approach is the use of distributed versions of Level 3 Basic Linear Algebra Subprograms as computational building blocks and the use of Basic Linear Algebra Communication Subprograms las communication building blocks for advanced architecture computers. The use of these low-level mathematical software libraries garantees the development of efficient, portable and scalable high-level algorithms and hides many details of the parallelism from the user's point of view. Numerical experiments on a simulated image restoration applications are shown. The parallel software has been tested on a 12 nodes IBM SP2 available at the Center for Research on Parallel Computing and Supercomputers in Naples (Italy).