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计算机工程 ›› 2012, Vol. 38 ›› Issue (22): 183-185. doi: 10.3969/j.issn.1000-3428.2012.22.045

• 图形图像处理 • 上一篇    下一篇

基于相似性判断的双边滤波改进算法

陈潇红   

  1. (浙江大学信息与电子工程学系,杭州 310027)
  • 收稿日期:2011-12-19 修回日期:2012-02-23 出版日期:2012-11-20 发布日期:2012-11-17
  • 作者简介:陈潇红(1987-),女,硕士研究生,主研方向:视频图像处理

Modified Bilateral Filtering Algorithm Based on Similarity Judgment

CHEN Xiao-hong   

  1. (Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China)
  • Received:2011-12-19 Revised:2012-02-23 Online:2012-11-20 Published:2012-11-17

摘要: The float exponential operation of bilateral filtering is not suitable for hardware implementation. In order to solve this problem, a modified bilateral filtering algorithm based on similarity judgment is proposed in this paper. Photometric similarity of every pixel in the filtering window is evaluated. Then these similar neighboring pixels are filtered by the modified bilateral filtering, which adopts reciprocal function instead of exponential function. Experimental results show that the modified bilateral filtering algorithm can balance the details and the flat areas, and it facilitates hardware implementation. The average Peak Signal Noise Ratio(PSNR) is 0.27 dB higher than bilateral filtering algorithm.

关键词: bilateral filtering, geometric closeness factor, photometric similarity factor, Gaussian noise, edge preserving, similarity judgment

Abstract: The float exponential operation of bilateral filtering is not suitable for hardware implementation. In order to solve this problem, a modified bilateral filtering algorithm based on similarity judgment is proposed in this paper. Photometric similarity of every pixel in the filtering window is evaluated. Then these similar neighboring pixels are filtered by the modified bilateral filtering, which adopts reciprocal function instead of exponential function. Experimental results show that the modified bilateral filtering algorithm can balance the details and the flat areas, and it facilitates hardware implementation. The average Peak Signal Noise Ratio(PSNR) is 0.27 dB higher than bilateral filtering algorithm.

Key words: bilateral filtering, geometric closeness factor, photometric similarity factor, Gaussian noise, edge preserving, similarity judgment

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