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

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

CLC Number: 

• TN911.73