北京生物醫(yī)學工程

基于RCSCT變換的DR圖像去噪及加速

DR image de-noising and acceleration based on recursive cycle spinning contourlet transformation

作者：林芳宇羅海周荷琴

單位：中國科學技術(shù)大學信息科學技術(shù)學院(合肥 230027)

關(guān)鍵詞： DR圖像去噪；Contourlet變換；遞歸循環(huán)平移；計算統(tǒng)一設(shè)備架構(gòu)

分類號：

出版年·卷·期（頁碼）：2012·31·3（245-250）

摘要：

目的數(shù)字化X線攝影(digital radiography，DR)圖像中的高斯噪聲對圖像質(zhì)量影響大，消除此類噪聲有利于提高圖像質(zhì)量以輔助醫(yī)生做出正確的診斷。方法為抑制DR圖像的高斯噪聲，首先采用遞歸循環(huán)平移與Contourlet變換結(jié)合的（recursive cycle spinning Contourlet transform，RCSCT）方法變換分解DR圖像，接著采用連續(xù)的二元軟閾值函數(shù)處理變換系數(shù)防止系數(shù)被過度扼殺，然后基于CUDA（compute unified device architecture,計算統(tǒng)一設(shè)備架構(gòu)）平臺對去噪方法加速。結(jié)果該方法提高了去噪后的圖像峰值信噪比，有效抑制了偽吉布斯現(xiàn)象,保留了更多的圖像細節(jié)信息，并且加速處理后運算耗時較短。結(jié)論本文方法比小波變換和Contourlet變換在保留視覺細節(jié)信息方面效果更優(yōu)，算法耗時少，實用性好。

Objective The influence of Gaussian noise on digital radiography(DR)image is great，and the removal of Gaussian noise is beneficial to the image quality and clinical diagnosis. Methods To suppress Gaussian noise of DR image，this paper first decomposes DR image based on recursive cycle spinning Contourlet transform(RCSCT)that combines recursive cycle spinning and Contourlet transform，then adopts continuous binary soft threshold function to process the transformed coefficients，which can prevent coefficients over killed，and subsequently accelerates the de-noising method based on compute unified device architecture(CUDA)platform. Results The experimental results show that the suggested method can obtain higher PSNR value，inhibit Gibbs-like phenomena，and preserve more image details with shorter time-consuming after acceleration. Conclusions The proposed method based on RCSCT is better than wavelet transform and Contourlet transform in practicability，time consuming and preservation of visual information.

參考文獻：

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