一种消除椒盐噪声的迭代自适应中值滤波算法
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摘要
针对传统中值滤波算法对高密度椒盐噪声图像滤波效果差的问题,基于循环迭代处理思想,提出一种消除椒盐噪声的迭代自适应中值滤波算法。在传统基于决策滤波方法基础上,所提算法自适应调整滤波窗口尺寸并计算滤波窗口内非椒盐像素中值以替换噪声像素,进而根据噪声密度自适应决定算法迭代次数,以完全消除椒盐噪声并恢复原始图像。仿真结果表明,对噪声密度为10%～99%的图像,与标准中值滤波及其4种改进算法相比,所提算法能较快消除椒盐噪声且可较好恢复原始图像细节。
The traditional median filtering algorithm has poor filtering effect on the images with high-density salt and pepper noise. Based on the theory of cyclic iterative processing, an iterative adaptive median filtering algorithm is proposed to remove the salt and pepper noise. Following the traditional filtering approach based on decision-making, the proposed algorithm adaptively adjusts the size of the filtering window and calculates the median of the non-salt and pepper pixels in the filtering window to replace the corrupted pixels. After that, the proposed algorithm adaptively determines the iteration number according to the noise density, so as to completely remove the salt and pepper noise and retrieve the original image. Simulation results demonstrate that, compared with the standard median filtering algorithm and four other improved algorithms, the proposed algorithm can remove the salt and pepper noise with less running time and can efficiently retrieve the details of the original image for the images with the noise density varying from 10% to 99%.
The traditional median filtering algorithm has poor filtering effect on the images with high-density salt and pepper noise. Based on the theory of cyclic iterative processing, an iterative adaptive median filtering algorithm is proposed to remove the salt and pepper noise. Following the traditional filtering approach based on decision-making, the proposed algorithm adaptively adjusts the size of the filtering window and calculates the median of the non-salt and pepper pixels in the filtering window to replace the corrupted pixels. After that, the proposed algorithm adaptively determines the iteration number according to the noise density, so as to completely remove the salt and pepper noise and retrieve the original image. Simulation results demonstrate that, compared with the standard median filtering algorithm and four other improved algorithms, the proposed algorithm can remove the salt and pepper noise with less running time and can efficiently retrieve the details of the original image for the images with the noise density varying from 10% to 99%.
引文
[1] KHAN S,LEE D H. An adaptive dynamically weighted median filter for impulse noise removal[J]. EURASIP Journal on Advances in Signal Processing,2017. doi:10.1186/s13634-017-0502-z.
[2]宗永胜,胡晓辉,张荣光.一种自适应双阈值中值滤波方法[J].小型微型计算机系统,2017,38(7):1642-1647.
[3]兰霞,刘欣鑫,沈焕锋,等.一种消除高密度椒盐噪声的迭代中值滤波算法[J].武汉大学学报:信息科学版,2017,42(12):1731-1737.
[4] ROY A,SINGHA J,MANAM L,et al. Combination of adaptive vector median filter and weighted mean filter for removal of high-density impulse noise from colour images[J]. IET Image Processing,2017,11(6):352-361.
[5] TUCKEY J W. Exploratory data analysis[M]. Boston:Addison-Wesley Pub. Co.,1977:163-182.
[6] SHRESTHA S. Image denoising using new adaptive based median filters[J]. Signal&Image Processing,2014,5(4):1-13.
[7] SRINIVASAN K S,EBENEZER D. A new fast and efficient decision-based algorithm for removal of high-density impulse noises[J]. IEEE Signal Processing Letters,2007,14(3):189-192.
[8] JAYARAJ V,EBENEZER D. A new switching-based median filtering scheme and algorithm for removal of highdensity salt and pepper noise in images[J]. EURASIP Journal on Advances in Signal Processing,2010. doi:10.1115/2010/690218.
[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] DAS J,DAS B,SAIKIA J,et al. Removal of salt and pepper noise using selective adaptive median filter[C]//International Conference on Accessibility to Digital World,IEEE,2017:203-206.
[11] KUNSOTH R,BISWAS M. Modified decision based median filter for impulse noise removal[C]//International Conference on Wireless Communications,Signal Processing and Networking,IEEE,2016:1316-1319.
[12] AHMED F,DAS S. Removal of high-density salt-andpepper noise in images with an iterative adaptive fuzzy filter using alpha-trimmed mean[J]. IEEE Transactions on Fuzzy Systems,2014,22(5):1352-1358.
[13]张成斌,王开福.基于形态开闭算子的高浓度椒盐噪声去除方法[J].计算机工程,2015,41(2):199-202.
[14] HUYNH-THU Q,GHANBARI M. Scope of validity of PSNR in image/video quality assessment[J]. Electronics Letters,2008,44(13):800-801.
[15] WANG Z,BOVIK A C,SHEIKH H R,et al. Image quality assessment:from error visibility to structural similarity[J]. IEEE Transactions on Image Processing,2004,13(4):600-612.
[2]宗永胜,胡晓辉,张荣光.一种自适应双阈值中值滤波方法[J].小型微型计算机系统,2017,38(7):1642-1647.
[3]兰霞,刘欣鑫,沈焕锋,等.一种消除高密度椒盐噪声的迭代中值滤波算法[J].武汉大学学报:信息科学版,2017,42(12):1731-1737.
[4] ROY A,SINGHA J,MANAM L,et al. Combination of adaptive vector median filter and weighted mean filter for removal of high-density impulse noise from colour images[J]. IET Image Processing,2017,11(6):352-361.
[5] TUCKEY J W. Exploratory data analysis[M]. Boston:Addison-Wesley Pub. Co.,1977:163-182.
[6] SHRESTHA S. Image denoising using new adaptive based median filters[J]. Signal&Image Processing,2014,5(4):1-13.
[7] SRINIVASAN K S,EBENEZER D. A new fast and efficient decision-based algorithm for removal of high-density impulse noises[J]. IEEE Signal Processing Letters,2007,14(3):189-192.
[8] JAYARAJ V,EBENEZER D. A new switching-based median filtering scheme and algorithm for removal of highdensity salt and pepper noise in images[J]. EURASIP Journal on Advances in Signal Processing,2010. doi:10.1115/2010/690218.
[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] DAS J,DAS B,SAIKIA J,et al. Removal of salt and pepper noise using selective adaptive median filter[C]//International Conference on Accessibility to Digital World,IEEE,2017:203-206.
[11] KUNSOTH R,BISWAS M. Modified decision based median filter for impulse noise removal[C]//International Conference on Wireless Communications,Signal Processing and Networking,IEEE,2016:1316-1319.
[12] AHMED F,DAS S. Removal of high-density salt-andpepper noise in images with an iterative adaptive fuzzy filter using alpha-trimmed mean[J]. IEEE Transactions on Fuzzy Systems,2014,22(5):1352-1358.
[13]张成斌,王开福.基于形态开闭算子的高浓度椒盐噪声去除方法[J].计算机工程,2015,41(2):199-202.
[14] HUYNH-THU Q,GHANBARI M. Scope of validity of PSNR in image/video quality assessment[J]. Electronics Letters,2008,44(13):800-801.
[15] WANG Z,BOVIK A C,SHEIKH H R,et al. Image quality assessment:from error visibility to structural similarity[J]. IEEE Transactions on Image Processing,2004,13(4):600-612.