Parallel Implementation of Image Filtering Algorithms in Multiprocessor Systems

Abstract

This paper studies parallel implementation of some image processing algorithms (linear filtering and order filtering) on shared memory multiprocessor system. Each of these algorithms can be parallelized using data partitioning of the image (pixels matrix), and each partition is assigned to a separated thread, running on a processor of the system. Input data (original image) and output data (resulted image) are global, shared variables, accessed by all threads during the execution. This implementation involves a low parallel overhead and the speedup tends to the maximal allowed speedup (equals the number of processors), when the dimension of image increases. The experimental results confirm this behavior and the fact that image-filtering algorithms are well suited for parallel execution on shared memory multiprocessors