计算机工程与科学
計算機工程與科學
계산궤공정여과학
COMPUTER ENGINEERING & SCIENCE
2010年
4期
49-51,66
,共4页
图像去噪%各向异性扩散方程%机群%并行算法%混合模型
圖像去譟%各嚮異性擴散方程%機群%併行算法%混閤模型
도상거조%각향이성확산방정%궤군%병행산법%혼합모형
image denoising%anisotropic diffusion equation%cluster%parallel algorithm%hybrid model
针对利用各向异性扩散方程的去噪模型在求解中存在计算量大、耗时长、影响实时性等缺点,本文充分利用并行知识,提出了有效的解决方案.即基于各向异性扩散去噪模型,设计工作站机群平台,对噪声图像进行条状重叠的数据划分,以便实现算法节点内与节点间的两级并行策略:在机群结点内部采用共享内存结构,机群节点间采用分布内存结构,以二者的最优结合实现并行的层次结构化,从而得到一种高效的多层次并行图像去噪算法.实验结果表明,在基于混合模型的并行环境下,该算法能在一定程度上提高原算法的计算效率,不仅有效地缩短了运行时间,而且仍能获得与其相当的图像去噪质量.
針對利用各嚮異性擴散方程的去譟模型在求解中存在計算量大、耗時長、影響實時性等缺點,本文充分利用併行知識,提齣瞭有效的解決方案.即基于各嚮異性擴散去譟模型,設計工作站機群平檯,對譟聲圖像進行條狀重疊的數據劃分,以便實現算法節點內與節點間的兩級併行策略:在機群結點內部採用共享內存結構,機群節點間採用分佈內存結構,以二者的最優結閤實現併行的層次結構化,從而得到一種高效的多層次併行圖像去譟算法.實驗結果錶明,在基于混閤模型的併行環境下,該算法能在一定程度上提高原算法的計算效率,不僅有效地縮短瞭運行時間,而且仍能穫得與其相噹的圖像去譟質量.
침대이용각향이성확산방정적거조모형재구해중존재계산량대、모시장、영향실시성등결점,본문충분이용병행지식,제출료유효적해결방안.즉기우각향이성확산거조모형,설계공작참궤군평태,대조성도상진행조상중첩적수거화분,이편실현산법절점내여절점간적량급병행책략:재궤군결점내부채용공향내존결구,궤군절점간채용분포내존결구,이이자적최우결합실현병행적층차결구화,종이득도일충고효적다층차병행도상거조산법.실험결과표명,재기우혼합모형적병행배경하,해산법능재일정정도상제고원산법적계산효솔,불부유효지축단료운행시간,이차잉능획득여기상당적도상거조질량.
According to the shortcomings of the anisotropic diffusion equation denoising model such as intensive calculations ,time consuming, affecting the real-timeness, etc, a full use of parallelism knowledge is made to put forward an effective solution.Based on the idea of the anisotropic diffusion equation denoising model, we design a cluster of workstations and divide the noise image into overlapping strips to realize the two-level-parallel strategies:the intra-node cluster using shared memory structure, the inter-node cluster using the distributed memory structure,the optimal combination of the two is used to achieve the parallel structure.Finally an effective hierarchical parallel algorithm for denoising images is proposed.The test result shows that , based on the hybrid-model parallel environment, the operating efficiency of the algorithm can be greatly enhanced,and the running time can be greatly reduced, meanwhile the comparable denoising quality can still be obtained.
