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基于自适应邻域概念的实时视频预处理算法 被引量:2

A Real-time Video Pre-filtering Algorithm Using Adaptive-neighborhood Statistics
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摘要 针对各种实时视频应用领域的实际要求,提出了一种新颖的实时视频预处理算法.该算法将自适应邻域的概念应用到视频信号预处理中,并融合线性均值滤波和非线性中值滤波两种方法的优点,能够同时有效地抑制加性高斯白噪声和稀疏的冲击噪声,并能完好地保持图像的边缘,因此,成功地弥补了传统算法的不足.此外,该算法较低的运算复杂度使得它可广泛应用于各种实时环境.仿真和实际使用结果表明,通过预处理后的图像的确获得了良好的视觉效果. Video pre-filtering is an important technique in all kinds of real-time video application fields and related areas. However, many proposed algorithms are too complex to be applied under real-time circumstances, and can not effectively suppress both additive white Gauss and impulsive noise without blurring the edges. We applied the concept of adaptive-neighborhood statistics to video pre-processing and proposed a novel algorithm. It not only retains the edge information of color images quite well but also has good restraint characteristics for both additive Gauss and impulsive noise. The emulation result shows that the algorithm provides better visual effect with very low computing complexity.
出处 《中国科学技术大学学报》 CAS CSCD 北大核心 2005年第2期154-160,共7页 JUSTC
关键词 视频预处理 彩色图像滤波 矢量中值滤波 高斯噪声 冲击噪声 video pre-filtering color image filtering vector median filtering Gauss noise impulsive noise
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  • 1Pitas I, Venetsanopoulos A N. Order statistics in digital image processing[A]. Proceed-ing of IEEE 80[C]. 1992:1 893-1 923.
  • 2Astola J, Haavisto P, Neuvo Y. Vector median filter[A]. Proceeding of IEEE 78[C].1990 : 678-689.
  • 3Paranjape R B, Rangayyan R M, Morrow W M. Adaptive neighborhood mean and median filtering[J]. Journal of Electronic Imaging,1994, 3(4) :360-367.
  • 4Paranjape R B, Rabie T F, Rangayyan R M.Image restoration by adaptive neighborhood noise subtraction[J]. Applied Optics. 1994,33(14);1 861-1 869.
  • 5Gonzalez R C, Woods R E. Digital Image Proeessing[M]. New York: Addison Wesley, 1992.
  • 6Milan Sonka, Vaclav Hlavac, Roger Boyle.Image Processing, Analysis, and Machine Vision, Second Edition[M]. California:Brooks Cole, 1998.
  • 7Ciuc M, Rangayyan R M, Zaharia T, et al.Filtering noise in color images using adaptive neighoborhood statistics[J]. Journal of Electronic Imaging, 2000, 9(4);484-494.
  • 8Rangayyan R M,Das A. Filtering multiplicative noise in images using adaptive region-based statistics[J]. Journal of Electronic Imaging, 1998, 7(1);222-230.

同被引文献16

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  • 2丁一,毛征,雷加印,卢青山.一种自适应双波门电视跟踪算法[J].火炮发射与控制学报,2007,28(1):44-46. 被引量:5
  • 3[1]Pitas I,Venetsanopoulos A N.Order statistics in digital image processing[A].Proceeding of IEEE,1992,80[C]:1893-1923
  • 4[2]Loupas T,Mcdicken W N,Allan P L.An adaptive weighted median filter for speckle suppression in medical ultrasound image[J].IEEE Trans.Circuits Syst.1989,36(1):129-135
  • 5[3]Paranjape R B,Rangayyan R M,Morrow W M.Adaptive neighborhood mean and median filtering[J].Journal of Electronic Imaging,1994,3(4):360-367
  • 6[4]Paranjape R B,Rabie T F,Rangayyan R M.Image restoration by adaptive neighborhood noise subtraction[J].Applied Optics,1994,33(14):1861-1869
  • 7[5]Durand F,Dorsey J.Fast Bilateral Filtering for the Display of High Dynamic Range Images[J].ACM Trans.on Graphics,2002,21(3):257-266
  • 8[7]Bennett E P,McMilan L.Video enhancement using per-pixel virtual exposures[J].ACM Trans.on Graphics 2005,24(3):845-852
  • 9[8]Michailovich O V,Tannenbaum A.Despeckling of Medical Ultrasound Images[J].IEEE Trans.UFFC,2006,53(1):64-78
  • 10S MTonissen,R J Evans.Performance of dynamic programming techniques for track-before-detect[J].IEEE Transactions on Aerospace and Electronic Systems,1996,32(4):1440-1451.

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