To prepare images for better segmentation, we need preprocessing applications, such as smoothing, to reduce\r\nnoise. In this paper, we present an enhanced computation method for smoothing 2D object in binary case. Unlike\r\nexisting approaches, proposed method provides a parallel computation and better memory management, while\r\npreserving the topology (number of connected components) of the original image by using homotopic\r\ntransformations defined in the framework of digital topology. We introduce an adapted parallelization strategy\r\ncalled split, distribute and merge (SDM) strategy which allows efficient parallelization of a large class of topological\r\noperators. To achieve a good speedup and better memory allocation, we cared about task scheduling and\r\nmanaging. Distributed work during smoothing process is done by a variable number of threads. Tests on 2D\r\ngrayscale image (512*512), using shared memory parallel machine (SMPM) with 8 CPU cores (2Ã?â?? Xeon E5405\r\nrunning at frequency of 2 GHz), showed an enhancement of 5.2 with cache success rate of 70%.
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