High Performance Color Image Processing in Multicore CPU using MFC Multithreading

Image processing is an engineering field where stored image data is readily available for parallel processing. Basically data processing algorithms developed in sequential approach are not capable of harnessing the computing power of individual cores present in a single-chip multicore processor. To utilize the multicore processor efficiently on windows platform for color image processing applications, a lock-free multithreading approach was developed using Visual C++ with Microsoft Foundation Class (MFC) support. This approach distributes the image data processing task on multicore Central Processing Unit (CPU) without using parallel programming framework like Open Multi-Processing (OpenMP) and reduces the algorithm execution time. In image processing, each pixel is processed using same set of high-level instruction which is time consuming. Therefore to increase the processing speed of the algorithm in a multicore CPU, the entire image data is partitioned into equal blocks and copy of the algorithm is applied on each block using separate worker thread. In this paper, multithreaded color image processing algorithms namely contrast enhancement using fuzzy technique and edge detection were implemented. Both the algorithms were tested on an Intel Core i5 Quad-core processor for ten different images of varying pixel size and their performance results are presented. A maximum of 71% computing performance improvement and speedup of about 3.4 times over sequential approach was obtained for large-size images using four thread model.