非局部的可切换滤波图像椒盐噪声去除方法
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摘要
针对图像被高强度椒盐噪声污染的问题,提出一种可切换的非局部去噪算法.首先将噪声图像切割为若干局部块作为算法的基本处理单位,设计块的预修复过程,以避免由于高噪声污染对局部块的干扰,保证相似度度量和模型估计过程的准确性;其次,在非局部范围内构造非局部滤波器,度量相似度并计算修复权值以进行噪声修复,得到全方位的图像去噪效果.实验结果表明,该算法较传统局部信息构建滤波器的方法,无论对低污染程度的图像,还是高污染程度的图像,在效果和图像衡量指标上均有一定的提升.
Aiming at the problem that the image contaminated by high intensity salt and pepper noise,the author proposed a non-local switchable denoising algorithm.First,the noisy image was cut into several local blocks as the basic processing unit of the algorithm,and the pre-repairing process of the blocks was designed to avoid the interference of the local blocks caused by the high noise pollution and ensure the similarity measure and the accuracy of the model estimation process.Then,a non-local filter was constructed in the non-local range,the author measured the similarity and calculated the repair weights to restore the noise,and obtained the omnidirectional image denoising effect.The experimental results show that compared with the traditional method of constructing filter based on local information,the proposed algorithm improves the performance and image measurement index of both low-pollution and high-pollution images.
Aiming at the problem that the image contaminated by high intensity salt and pepper noise,the author proposed a non-local switchable denoising algorithm.First,the noisy image was cut into several local blocks as the basic processing unit of the algorithm,and the pre-repairing process of the blocks was designed to avoid the interference of the local blocks caused by the high noise pollution and ensure the similarity measure and the accuracy of the model estimation process.Then,a non-local filter was constructed in the non-local range,the author measured the similarity and calculated the repair weights to restore the noise,and obtained the omnidirectional image denoising effect.The experimental results show that compared with the traditional method of constructing filter based on local information,the proposed algorithm improves the performance and image measurement index of both low-pollution and high-pollution images.
引文
[1]杨成佳.图像去噪及其效果评估若干问题研究[D].长春:吉林大学,2016.(YANG Chengjia.Study on Image Denoising and Its Effect Evaluation[D].Changchun:Jilin University,2016.)
[2]王贵君,杨永强.基于高概率椒盐噪声的模糊滤波器在图像恢复中的算法设计[J].电子学报,2015,43(1):24-29.(WANG Guijun,YANG Yongqiang.Alogrithm Design of Fuzzy Filter Based on Salt-and-Pepper Noise with High Probabillity in Image Restoration[J].Acta Electronica Sinica,2015,43(1):24-29.)
[3]左平,王洋,申延成.一种基于全变差正则化与小波包变换的图像去噪算法[J].吉林大学学报(理学版),2014,52(1):81-85.(ZUO Ping,WANG Yang,SHEN Yancheng.Image Denoising Algorithm Based on Wavelet Packet Transform and Total Variation Model[J].Journal of Jilin University(Science Edition),2014,52(1):81-85.)
[4]ASTOLA J,KUOSMANEEN P.Fundamentals of Nonlinear Digital Filtering[M].Boca Raton,FL:CRCPress,1997.
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[12]ZHANG Shuqun,KARIM M A.A New Impulse Detector for Switching Median Filter[J].IEEE Signal Processing Letter,2002,9(11):360-363.
[13]ENG H L,MA K K.Noise Adaptive Soft Switching Median Filter[J].IEEE Transactions on Image Processing,2001,10(2):242-251.
[14]JAFAR I F,ALNA’MNEH R A,DARABKH K A.Efficient Improvements on the BDND Filtering Algorithm for the Removal of High-Density Impulse Noise[J].IEEE Transactions on Image Processing,2013,22(3):1223-1231.
[15]TOH K K V,IBRAHIM H,MAHYUDDIN M N.Salt-and-Pepper Noise Detection and Reduction Using Fuzzy Switching Median Filter[J].IEEE Transactions on Consumer Electronics,2008,54(4):1956-1961.
[16]MADHU S,RAJU N G.A New Fuzzy-Based Decision Algorithm for High-Density Impulse Noise Removal[J].Signal Image Video Process,2012,6(4):579-595.
[17]BUADES A,COLL B,MOREL J M.A Non-local Algorithm for Image Denoising[C]//IEEE International Conference on Computer Vision and Pattern Recognition.Washington D C:IEEE Computer Society,2005:60-65.
[18]BUADES A,COLL B,MOREL J M.Self-Similarity-Based Image Denoising[J].Communications of the ACM,2011,54(5):109-117.
[19]DABOV K,FOI A,KATKOVNIK V,et al.Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering[J].IEEE Transactions on Image Processing,2007,16(8):2080-2095.
[20]DABOV K,FOI A,KATKOVNIK V,et al.A Nonlocal Transform-Domain Filter for Volumetric Data Denoising and Reconstruction[J].IEEE Transactions on Image Processing,2013,22(1):119-133.
[2]王贵君,杨永强.基于高概率椒盐噪声的模糊滤波器在图像恢复中的算法设计[J].电子学报,2015,43(1):24-29.(WANG Guijun,YANG Yongqiang.Alogrithm Design of Fuzzy Filter Based on Salt-and-Pepper Noise with High Probabillity in Image Restoration[J].Acta Electronica Sinica,2015,43(1):24-29.)
[3]左平,王洋,申延成.一种基于全变差正则化与小波包变换的图像去噪算法[J].吉林大学学报(理学版),2014,52(1):81-85.(ZUO Ping,WANG Yang,SHEN Yancheng.Image Denoising Algorithm Based on Wavelet Packet Transform and Total Variation Model[J].Journal of Jilin University(Science Edition),2014,52(1):81-85.)
[4]ASTOLA J,KUOSMANEEN P.Fundamentals of Nonlinear Digital Filtering[M].Boca Raton,FL:CRCPress,1997.
[5]HWANG H,HADDED R A.Adaptive Median Filter:New Algorithms and Results[J].IEEE Transactions on Image Processing,1995,4(4):499-502.
[6]SRINIVASAN K S,EBENEZER D.A New Fast and Efficient Decision Based Algorithm for Removal of High Density Impulse Noise[J].IEEE Signal Process Letter,2007,14(3):189-192.
[7]ZHOU Y Y,YE Z F,HUANG J J.Improved Decision-Based Detail-Preserving Variational Method for Removal of Random-Valued Impulse Noise[J].IET Image Processing,2012,6(7):976-985.
[8]AISWARYA K,JAYARAJ V,EBENEZER D.A New and Efficient Algorithm for the Removal of High Density Salt and Pepper Noise in Images and Videos[C]//Proceedings of the Second International Conference on Computer Modeling and Simulation.Washington D C:IEEE Computer Society,2010:409-413.
[9]ESAKKIRAJAN S,VEERAKUMAR T,SUBRAMANYAM A N,et al.Removal of High Density Salt and Pepper Noise through Modified Decision Based Unsymmetric Trimmed Median Filter[J].IEEE Signal Processing Letters,2011,18(5):287-290.
[10]LU Peizhong,WANG Wei.An Efficient Switching Median Filter Based on Local Outlier Factor[J].IEEE Signal Processing Letter,2011,18(10):551-554.
[11]NG P E,MA K K.A Switching Median Filter with Boundary Discriminative Noise Detection for Extremely Corrupted Images[J].IEEE Transactions on Image Processing,2006,15(6):1506-1516.
[12]ZHANG Shuqun,KARIM M A.A New Impulse Detector for Switching Median Filter[J].IEEE Signal Processing Letter,2002,9(11):360-363.
[13]ENG H L,MA K K.Noise Adaptive Soft Switching Median Filter[J].IEEE Transactions on Image Processing,2001,10(2):242-251.
[14]JAFAR I F,ALNA’MNEH R A,DARABKH K A.Efficient Improvements on the BDND Filtering Algorithm for the Removal of High-Density Impulse Noise[J].IEEE Transactions on Image Processing,2013,22(3):1223-1231.
[15]TOH K K V,IBRAHIM H,MAHYUDDIN M N.Salt-and-Pepper Noise Detection and Reduction Using Fuzzy Switching Median Filter[J].IEEE Transactions on Consumer Electronics,2008,54(4):1956-1961.
[16]MADHU S,RAJU N G.A New Fuzzy-Based Decision Algorithm for High-Density Impulse Noise Removal[J].Signal Image Video Process,2012,6(4):579-595.
[17]BUADES A,COLL B,MOREL J M.A Non-local Algorithm for Image Denoising[C]//IEEE International Conference on Computer Vision and Pattern Recognition.Washington D C:IEEE Computer Society,2005:60-65.
[18]BUADES A,COLL B,MOREL J M.Self-Similarity-Based Image Denoising[J].Communications of the ACM,2011,54(5):109-117.
[19]DABOV K,FOI A,KATKOVNIK V,et al.Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering[J].IEEE Transactions on Image Processing,2007,16(8):2080-2095.
[20]DABOV K,FOI A,KATKOVNIK V,et al.A Nonlocal Transform-Domain Filter for Volumetric Data Denoising and Reconstruction[J].IEEE Transactions on Image Processing,2013,22(1):119-133.