计算机科学 ›› 2013, Vol. 40 ›› Issue (7): 262-265.

• 图形图像与模式识别 • 上一篇    下一篇

基于像素层标识点的双边滤波快速实现

郑丽萍,李俊青,于承敏,张民   

  1. 聊城大学计算机学院 聊城252059;聊城大学计算机学院 聊城252059;聊城大学计算机学院 聊城252059;聊城大学计算机学院 聊城252059
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金项目(61104179),山东省教育厅资助

Fast Implementation of Bilateral Filtering with Identification Point in Pixel Layer

ZHENG Li-ping,LI Jun-qing,YU Cheng-min and ZHANG Min   

  • Online:2018-11-16 Published:2018-11-16

摘要: 双边滤波能在去除噪声的同时有效地保留图像的边缘信息。但双边滤波的时间复杂度高,执行时间长。根据近似层和亮度分层的概念,利用标识点及像素层来快速实现双边滤波。首先根据灰度差值划分图像的像素层,然后在像素层上选择标识点,并利用标识点计算像素层的滤波值,最后通过线性插值获得各像素点的滤波值,并输出滤波图像。该改进算法称为标识点双边滤波(Identification Bilateral Filtering)。在实验中分别对灰度和彩色图像进行了双边滤波。实验结果表明,IBF算法执行时间短,并能获得较好的滤波效果。

关键词: 双边滤波,像素层,标识点,欧氏距离 中图法分类号TP391文献标识码A

Abstract: Bilateral filtering is a technique to delete images noise while effectively preserving edges.The nave implementation of the bilateral filtering can be extremely slow.The time complexity is high.According to concepts of appro-ximate layer and intensity layer,a improved bilateral filtering was proposed.This improved algorithm uses identification and pixel layer to realize Bilateral Filtering.This improved algorithm is called identification Bilateral Filtering(IBF).At first,the pixel layer with gray D-value was specified,then identification point in pixel layer was choosen,and the filtering value of every pixel layers with identification point was computed.At last,linear interpolation was used to compute filtering value of pixels and output filtered image.Gray image and color image were taken as research objects in experiment.Experiment results show that the IBF algorithm has short executing time and has a good filtering result.

Key words: Bilateral filtering,Pixel layer,Identification point,Euclidean distance

[1] Overton K J,Weymouth T E.A noise reducing preprocessing algorithm[A]∥Proceedings of IEEE Computer Science Confe-rence on Pattern Recognition and Image Processing[C].Chicago,Illinois,USA,1979:498-507
[2] Pham T Q,van Vliet L J.Separable bilateral filtering for fast video preprocessing[C]∥Proceedings of the IEEE International Conference on Multimedia and Expo.2005
[3] Weiss B.Fast median and bilateral filtering[J].ACM Transactions on Graphics,2006,25(3):519-526
[4] Durand F,Dorsey J.Fast bilateral filtering for the display of high-dynamic-range images[J].ACM Transactions on Grap-hics,2002,21(3):257-266
[5] Pairs S,Durand F.A fast approximation of the bilateral filter using a signal processing approach[J].International Journal of Computer Vision,2009,81(1):24-52
[6] Fattal R,Agrawala M,Rusinkiewicz S.Multiscale shape and detail enhancement from multi-light image collections[J].ACM Transactions on Graphics,2007,26(3):51
[7] 李凡,刘上乾,秦翰林.自适应双边滤波红外弱小目标检测方法[J].光子学报,2010,39(6)
[8] Fleishman S,Drori I,Cohen-Or D.Bilateral mesh denoising[C]∥Proc.ACM SIGGRAPH.San Diego,CA,July 2003:950-953
[9] Jones T R,Durand F,Desbrun M.Non-iterative feature-preserving mesh smoothing[C]∥Proc ACM SIGGRAPH.San Diego,CA,July 2003:943-949
[10] Xiao J,Cheng H,Sawhney H,et al.Bilateral filtering-based optical flow estimation with occlusion detection[C]∥Proc.Euro-pean Conference on Computer Vision. Vol.1, Graz,Austria,May 2006:211-224
[11] Zhang M,Gunturk B K.Multiresolution bilateral filtering for image denoising[J].IEEE Trans.Image Processing,2008,17(12):2324-2333
[12] Zhang M,Gunturk B K.Compression artifact reduction with adaptive bilateral filtering[C]∥Proc.SPIE Electronic Imaging.vol.7257,San Jose,CA,72571A,2009
[13] Yang Q X,Tan K H,Ahuja N.Real-time O(1) bilateral filtering[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D C,IEEE Computer Society-Press,2009:557-564

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