Research Of Multi-core Parallel Image Segmentation Algorithm Based On Multiresoluion Image Pyramid Combined With FCM

With the development of image acquisition technology, people can gain the higher and higher resolution image. It is useful to efficiently extract a large number of identifying information in the high resolution images for the application of Image Engineering. The traditional multiresolution image pyramid utilizes the low-pass filter technique, which easily causes the number of segmentation regions not equal to the true number of objects which really exist in the high resolution image; when the algorithm of fuzzy c-mean (FCM) is applied to segment the image, it may ignore the spatial context and also has the large complexity of time and space. How to improve the segmentation efficiency of large image is becoming a difficult problem.In this paper, a novel technique is proposed, which combines the multiresolution image pyramid based on the orthogonal wavelet decomposition with the FCM algorithm. This paper integrally analyses the muti-core parallel feasibility of the orthogonal wavelet decomposition, the multiresolution image pyramid segmentation algorithm and FCM algorithm, designs the multi-core parallel model of P-FCM which is the combination of the multiresolution image pyramid amd FCM, and the parallel language of OpenMP is adopted to achieve this model. Experiment testifies that this model preferably improves the efficiency of image segmentation under the promise of segmentation quality.The main contents of this paper can be summarized as follows:①Discusses and analyzes the image segmentation technique research background, practical application of significance, research status and the basic knowledge of image processing, then introduces the development of multi-core parallelism and the related technologies.②Aiming at the design method of traditional image pyramid is high computational complexity and the low efficiency of segmentation, a novel algorithm of multi-core parallel orthogonal wavelet decomposition is applied to design the pyramidal structure, and proposes the multi-core parallel model of image segmentation using multiresolution image pyramid (P- Multi-core Parallel Pyramidal Model).③Aiming at the problem of over - or under -segmentation using the multiresolution image pyramid, this paper introduces the algorithm of FCM, designs its multi-core parallel model, and presents the multi-core parallel model of P-FCM, which combines the multi-core parallel model of P with the multi-core parallel model of FCM. In addition, for the original image data preprocessing, the parallel method of rectangular block is used to divide the original image data.④The language of OpenMP is adopted to program the multi-core parallel model of P-FCM, and analyses the Speedup of the P-FCM multi-core parallel model when this algorithm is dealing with the images of different size and different resolution.⑤Experiments testify that the algorithm of P-FCM could achieve almost linear SpeedUP with the increase of CPU's number, especially for the high resolution large image (over 1MB) segmentation.The multi-core parallel model of P-FCM proposed by this paper could reduce the computational complexity, improve the efficiency of image segmentation and meet the requirements of strong real-time and high accuracy in the applications of Image Engineering.