计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
18期
152-155,161
,共5页
图像去噪%马尔可夫链蒙特卡洛方法(MCMC)%方差估计%预处理%并行处理
圖像去譟%馬爾可伕鏈矇特卡洛方法(MCMC)%方差估計%預處理%併行處理
도상거조%마이가부련몽특잡락방법(MCMC)%방차고계%예처리%병행처리
image denoising%Markov Chain Monte Carlo(MCMC)%variance estimation%pretreatment%parallel processing
图像去噪是许多图像处理任务的前提。马尔可夫链蒙特卡洛图像去噪算法是很重要的一种图像去噪方法，但去噪后图像存在明显斑点，在高噪声情况下去噪效果不理想，实际应用中需要进行噪声方差估计，运算速度慢。提出两步去噪方法，用均值滤波对噪声图像进行预处理，估计预处理后图像噪声方差，进行MCMC图像去噪；为充分利用多核处理器的硬件资源，研究了将MCMC算法进行并行编程，提高了程序的运行速度。实验表明两步去噪方法减少了斑点、提高了信噪比；并行实现提高了运算效率。
圖像去譟是許多圖像處理任務的前提。馬爾可伕鏈矇特卡洛圖像去譟算法是很重要的一種圖像去譟方法，但去譟後圖像存在明顯斑點，在高譟聲情況下去譟效果不理想，實際應用中需要進行譟聲方差估計，運算速度慢。提齣兩步去譟方法，用均值濾波對譟聲圖像進行預處理，估計預處理後圖像譟聲方差，進行MCMC圖像去譟；為充分利用多覈處理器的硬件資源，研究瞭將MCMC算法進行併行編程，提高瞭程序的運行速度。實驗錶明兩步去譟方法減少瞭斑點、提高瞭信譟比；併行實現提高瞭運算效率。
도상거조시허다도상처리임무적전제。마이가부련몽특잡락도상거조산법시흔중요적일충도상거조방법，단거조후도상존재명현반점，재고조성정황하거조효과불이상，실제응용중수요진행조성방차고계，운산속도만。제출량보거조방법，용균치려파대조성도상진행예처리，고계예처리후도상조성방차，진행MCMC도상거조；위충분이용다핵처리기적경건자원，연구료장MCMC산법진행병행편정，제고료정서적운행속도。실험표명량보거조방법감소료반점、제고료신조비；병행실현제고료운산효솔。
Image denoising is a prerequisite for the many processing tasks of image. Markov Chain Monte Carlo algo-rithm is an important method of image denoising. However, the method has some problems such that the denoised image has obvious spots, the denoising image corrupted by heavy noise is not satisfactory, the noise variance needs to be estimated in practical application, and the operation speed of this method is slow. This paper proposes a two-step denoising method. It preprocesses the noise image using the mean filter. It estimates the pretreated image noise variance. It uses the MCMC image denoising method. To take full advantage of multi-core processor resources, this paper studies the parallel program-ming of MCMC algorithm. The multi-core program increases the speed of MCMC algorithm. The experiments show that the denoising method given in this paper reduces spots and improves the signal-to-noise ratio. Parallel processing can make the algorithm more efficient.
