Title :
Adaptive support-window approximation to bilateral filtering
Author :
Guo-Shiang Lin ; Chun-Yu Chen ; Chun-Ting Kuo ; Wen-Nung Lie ; Kai-Che Liu
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Da-Yeh Univ., Taiwan
Abstract :
In this paper, a computation-efficient adaptive support-window scheme is proposed to approximate the conventional bilateral filtering. The difference is that the pixel-wise weights in bilateral filter are thresholded to be only 0 or 1. This results in an adaptive support window, depending on the local image structure of the anchor pixel. A cross-based algorithm is devised to achieve adaptive support window. Experiments show that both noise removal and edge-preserving can be also achieved using our proposed filter. By computing integral images during data aggregation, our algorithm is capable of achieving constant-time complexity regardless of the shape of the support window. Experiments demonstrate that our proposed computing scheme can reduce up to 98% of execution time with respect to the traditional bilateral filter.
Keywords :
computational complexity; image processing; low-pass filters; smoothing methods; anchor pixel; bilateral filtering; computation-efficient adaptive support-window approximation scheme; cross-based algorithm; data aggregation; edge-preserving; integral images; local image structure; noise removal; pixel-wise weights; time complexity; Approximation algorithms; Approximation methods; Filtering; Filtering algorithms; Image color analysis; Image edge detection; Noise;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4