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