基于OpenMP的并行小波图像分割实验研究

Priya P. Sajan, S. Sushanth Kumar
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引用次数: 2

摘要

图像分割是一项计算成本高且复杂的任务,由于高分辨率图像量的巨大增加,其性能不断受到挑战。如今,使用OpenMP的共享内存多核并行编程体系结构由于其巨大的处理性能、较低的复杂性和最低的成本,正在成为通用和科学计算的一个有吸引力的计算平台。随着多核架构技术的进步,图像分割过程的快速执行成为一个重要的标准。提出了一种基于OpenMP的并行小波图像分割的实验方法。重点探讨了基于共享内存架构的OpenMP小波图像分割的计算量和任务并行性,具有良好的处理速度和准确的分割结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental study on parallel wavelet based image segmentation using OpenMP
Image segmentation is a computationally expensive and complex task that continuously focuses on performance challenges due to tremendous increase in the volume of high resolution images. Nowadays, shared memory multicore parallel programming architectures using OpenMP is emerging as an attractive computing platform for both general purpose and scientific computations due to their immense processing performance, less complexity and minimal cost. Faster execution of image segmentation process is emerging as an important criterion with the technical advancements in multicore architectures. This paper proposes an experimental method for parallelizing wavelet based image segmentation using OpenMP. Emphasis is also made on exploring the computational data and task parallelism in wavelet based image segmentation using OpenMP on shared memory architecture with promising processing speed and accurate segmentation result.
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