基于开关二级检测的图像椒盐噪声滤波算法
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摘要
鉴于开关中值滤波在椒盐噪声检测和去除方面的应用合理性,本文分别设计实现了基于信号局部差异性和基于信号方向差异性的椒盐噪声检测算法。这两种算法均属于二级噪声检测方法,且第一级检测手段都是基于灰度范围准则。两种算法的不同点主要体现在第二级检测算法上,前者基于局部差别准则,后者基于方向差别准则。在方法评价部分,首先通过分析和实验确定两种算法的最优参数设置;然后通过对不同噪声密度的测试图像去噪来评价两种算法的去噪效果。结果表明:基于方向差异性的算法比基于局部差异性的算法具有更好的性能,且两种算法的去噪效果都与噪声密度成反比。需要注意的是,这两种算法都容易将图像中的细微边缘或细节像素误判为噪声点,即在噪声的检测过程中,只能避免对图像中主要边缘和轮廓像素的误判,还无法对图像中的细微边缘和细节进行精确判定,这也是开关二级噪声滤波算法今后的主要改进方向。另外,算法效率测试结果表明两种算法具有相似的计算时间,从而验证了两者之间的算法结构相似性。
Switch median filters are very suitable for detection and removal of the salt and pepper noise.An algorithm based on signal local difference and an algorithm based on signal directional difference for detecting salt and pepper noise were designed in this article.Both of them belong to twostage noise detection algorithms,and the first-stage detection for both is based on gray-scale range cri-terion.The difference between the two algorithms embodies in the second-stage detection.The former is based on local difference criterion,and the later is based on directional difference criterion.In the section of algorithm evaluation,first,the optimal parameter settings for the two algorithms were determined through analysis and experiments.Then,the denoising effects of the two algorithms were evaluated by denoising the test images with different noise density.The evaluation results show that the algorithm based on directional difference has better performance than the algorithm based on local difference.For both of the two algorithms,the denoising effects are inversely proportional to noise density.But more importantly,the two algorithms may be prone to misjudge the image-edge pixels or detail pixels as noise points.This will be the main improvement direction of the switch median filtering algorithm in the future.Finally,the two algorithms have the similar computational efficiency.It verifies the structural similarity between them.
Switch median filters are very suitable for detection and removal of the salt and pepper noise.An algorithm based on signal local difference and an algorithm based on signal directional difference for detecting salt and pepper noise were designed in this article.Both of them belong to twostage noise detection algorithms,and the first-stage detection for both is based on gray-scale range cri-terion.The difference between the two algorithms embodies in the second-stage detection.The former is based on local difference criterion,and the later is based on directional difference criterion.In the section of algorithm evaluation,first,the optimal parameter settings for the two algorithms were determined through analysis and experiments.Then,the denoising effects of the two algorithms were evaluated by denoising the test images with different noise density.The evaluation results show that the algorithm based on directional difference has better performance than the algorithm based on local difference.For both of the two algorithms,the denoising effects are inversely proportional to noise density.But more importantly,the two algorithms may be prone to misjudge the image-edge pixels or detail pixels as noise points.This will be the main improvement direction of the switch median filtering algorithm in the future.Finally,the two algorithms have the similar computational efficiency.It verifies the structural similarity between them.
引文
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[9]陈健,郑绍华,余轮,等.基于方向的多阈值自适应中值滤波改进算法[J].电子测量与仪器学报,2013,27(2):156-161.CHEN J,ZHENG S H,YU L,et al.Improved algorithm for adaptive median filter with multi-threshold based on directional information[J].Journal of Electronic Measurement and Instrument,2013,27(2):156-161.(in Chinese)
[10]常丹华,杨峰明,赵国立,等.基于二级检测的椒盐噪声滤除算法[J].激光与红外,2012,42(1):100-104.CHANG D H,YANG F M,ZHAO G L,et al.Salt and pepper noise filtering algorithm based on two stage noise detection[J].Laser&Infrared,2012,42(1):100-104.(in Chinese)
[11]陈健,郑绍华.基于方向中值的图像椒盐噪声检测算法[J].计算机应用,2012,32(10):2790-2792.CHEN J,ZHENG S H.Salt and pepper noise detection algorithm based on directional median[J].Journal of Computer Applications,2012,32(10):2790-2792.(in Chinese)
[12]汪祖辉,孙刘杰,邵雪,等.一种结合小波变换和维纳滤波的图像去噪算法[J].包装工程,2016,37(13):173-178.WANG Z H,SUN L J,SHAO X,et al.An image denoising algorithm combined with wavelet transform and wiener filtering[J].Packaging Engineering,2012,37(13):173-178.(in Chinese)
[13]张闯,迟健男,张朝晖,等.基于边缘检测与双边滤波的彩色图像去噪[J].电子学报,2010,38(8):1776-1783.ZHANG C,CHI J N,ZHANG Z H,et al.Removing noise of color images based on edge detection and bilateral filter[J].Acta Electronica Sinica,2010,38(8):1776-1783.
[14]王娜,朱明,陈广学.一种基于双滤波的空间图像色域映射算法[J].电子学报,2016,44(8):1924-1931.WANG N,ZHU M,CHEN G X.A spatial gamut mapping algorithm based on bilateral filter[J].Acta Electronica Sinica,2016,44(8):1924-1931.
[15]ZHU M,WANG N,HARDEBERG J Y.Spatial gamut mapping based on guided filter to preserve spatial luminance variations[J].Journal of Imaging Science&Technology,2017,61(2):220506-1-10.
[2]宋宇,李满天,孙立宁.基于相似度函数的图像椒盐噪声自适应滤除算法[J].自动化学报,2007,33(5):474-479.SONG Y,LI M T,SUN L N.Image salt&pepper noise self-adaptive suppression algorithm based on similarity function[J].Acta Automatica Sinica,2007,33(5):474-479.(in Chinese)
[3]王红梅,李言俊,张科.基于极值检测的图像滤波算法[J].激光与红外,2007,37(10):1117-1119.WANG H M,LI Y J,ZHANG K.An image filtering algorithm based on extremum detection[J].Laser&Infrared,2007,37(10):1117-1119.(in Chinese)
[4]BROWNRIGG D.The weighted median filter[J].Communications of the Acm,1984,27(8):807-818.
[5]YANG R,LIN Y,GABBOUJ M,et al.Optimal weighted median filtering under structural constraints[J].IEEETransactions on Signal Processing,1995,43(3):591-604.
[6]HWANG H,HADDAD R A.Adaptive median filters:new algorithms and results[J].IEEE Transactions on Image Processing,1995,4(4):499-502.
[7]倪巨敏,叶懋东,陈孝春.一种改进的自适应中值滤波算法[J].中国图象图形学报,2006,11(5):672-678.NI C M,YE M D,CHEN X C.An improved adaptive median filter algorithm[J].Journal of Image and Graphics,2006,11(5):672-678.(in Chinese)
[8]乔坤,郭朝勇,毛东.一种去除椒盐噪声的自适应开关中值滤波算法[J].计算机应用与软件,2011,28(10):253-256.QIAO K,GUO C Y,MAO D.An adaptive switch median filtering algorithm for salt and pepper noise[J].Computer Applications and Software,2011,28(10):253-256.(in Chinese)
[9]陈健,郑绍华,余轮,等.基于方向的多阈值自适应中值滤波改进算法[J].电子测量与仪器学报,2013,27(2):156-161.CHEN J,ZHENG S H,YU L,et al.Improved algorithm for adaptive median filter with multi-threshold based on directional information[J].Journal of Electronic Measurement and Instrument,2013,27(2):156-161.(in Chinese)
[10]常丹华,杨峰明,赵国立,等.基于二级检测的椒盐噪声滤除算法[J].激光与红外,2012,42(1):100-104.CHANG D H,YANG F M,ZHAO G L,et al.Salt and pepper noise filtering algorithm based on two stage noise detection[J].Laser&Infrared,2012,42(1):100-104.(in Chinese)
[11]陈健,郑绍华.基于方向中值的图像椒盐噪声检测算法[J].计算机应用,2012,32(10):2790-2792.CHEN J,ZHENG S H.Salt and pepper noise detection algorithm based on directional median[J].Journal of Computer Applications,2012,32(10):2790-2792.(in Chinese)
[12]汪祖辉,孙刘杰,邵雪,等.一种结合小波变换和维纳滤波的图像去噪算法[J].包装工程,2016,37(13):173-178.WANG Z H,SUN L J,SHAO X,et al.An image denoising algorithm combined with wavelet transform and wiener filtering[J].Packaging Engineering,2012,37(13):173-178.(in Chinese)
[13]张闯,迟健男,张朝晖,等.基于边缘检测与双边滤波的彩色图像去噪[J].电子学报,2010,38(8):1776-1783.ZHANG C,CHI J N,ZHANG Z H,et al.Removing noise of color images based on edge detection and bilateral filter[J].Acta Electronica Sinica,2010,38(8):1776-1783.
[14]王娜,朱明,陈广学.一种基于双滤波的空间图像色域映射算法[J].电子学报,2016,44(8):1924-1931.WANG N,ZHU M,CHEN G X.A spatial gamut mapping algorithm based on bilateral filter[J].Acta Electronica Sinica,2016,44(8):1924-1931.
[15]ZHU M,WANG N,HARDEBERG J Y.Spatial gamut mapping based on guided filter to preserve spatial luminance variations[J].Journal of Imaging Science&Technology,2017,61(2):220506-1-10.