Parallel Implementations of Image Processing Algorithms on Multi-Core

The broad introduction of multi-core processors into computing has brought a great opportunity to deploy computationally demanding applications such as signal and image processing on parallel computing platforms. However it is not an easy task to decompose a computational problem into sub-problems to explore the massive parallelism provided by multi-core processors. In this paper, we study the cubic convolution interpolation algorithm for image processing. We shall parallelize the algorithm using the parallel programming tools TBB and OpenMP, and compare the performance of parallel and sequential implementations. Our experiments show that the parallel implementation of the algorithm using results in a speed-up about 200% compared with sequential implementation on a Dual-core processor, while a speed-up about 400% on a Quad-core processor.