發(fā)布時(shí)間：2018-03-14 03:36

  本文選題：圖像去噪　切入點(diǎn)：非下采樣Shearlet變換　出處：《信號(hào)處理》2017年11期 　論文類型：期刊論文

【摘要】：為消除基于圖像處理的刀具磨損檢測(cè)中的圖像噪聲,提出了結(jié)合非下采樣Shearlet變換(Non-subsampled Shearlet Transform,NSST)和快速非局部均值(Fast Non-local Means,FNLM)濾波的圖像去噪方法。首先,利用基于決策的非對(duì)稱剪切中值(Decision Based Un-symmetric Trimmed Median,DBUTM)方法濾除圖像中的椒鹽噪聲;然后,對(duì)圖像進(jìn)行NSST多尺度分解,得到一個(gè)低頻子帶和一系列高頻子帶;最后,分別使用FNLM濾波和各向異性擴(kuò)散模型調(diào)整低頻和高頻子帶系數(shù),并由調(diào)整后的各子帶系數(shù)重構(gòu)出噪聲濾除后的圖像。實(shí)驗(yàn)結(jié)果表明,與基于小波的閾值收縮方法、基于Contourlet的全變差模型結(jié)合各向異性擴(kuò)散方法、基于NSST和標(biāo)準(zhǔn)非局部均值濾波方法相比,本文方法在主觀視覺去噪效果、峰值信噪比、結(jié)構(gòu)相似度以及處理速度等4個(gè)方面性能更優(yōu)。
[Abstract]:In order to eliminate image noise in tool wear detection based on image processing, an image denoising method combining non-subsampled Shearlet transform NSST with fast nonlocal mean fast Non-local means FNLM filter is proposed. The decision Based Un-symmetric Trimmed DBUTM method is used to filter the salt and pepper noise in the image. Then, a low frequency subband and a series of high frequency subbands are obtained by the NSST multiscale decomposition of the image. The low frequency and high frequency subband coefficients are adjusted by FNLM filter and anisotropic diffusion model respectively, and the noise filtered images are reconstructed from the adjusted subband coefficients. The experimental results show that the proposed method is similar to the wavelet based threshold shrinkage method. The total variation model based on Contourlet combined with anisotropic diffusion method, compared with the standard non-local mean filtering method based on NSST, is applied to the subjective vision de-noising, peak signal-to-noise ratio (PSNR). The performance of structure similarity and processing speed is better.
【作者單位】： 南京航空航天大學(xué)電子信息工程學(xué)院;西華大學(xué)制造與自動(dòng)化省高校重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(61573183) 西華大學(xué)制造與自動(dòng)化省高校重點(diǎn)實(shí)驗(yàn)室開放課題(S2jj2014-028)
【分類號(hào)】：TG71;TP391.41
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本文編號(hào)：1609428