Title :
Constant time O(1) bilateral filtering
Author_Institution :
Mitsubishi Electr. Res. Lab., Cambridge, MA
Abstract :
This paper presents three novel methods that enable bilateral filtering in constant time O(1) without sampling. Constant time means that the computation time of the filtering remains same even if the filter size becomes very large. Our first method takes advantage of the integral histograms to avoid the redundant operations for bilateral filters with box spatial and arbitrary range kernels. For bilateral filters constructed by polynomial range and arbitrary spatial filters, our second method provides a direct formulation by using linear filters of image powers without any approximation. Lastly, we show that Gaussian range and arbitrary spatial bilateral filters can be expressed by Taylor series as linear filter decompositions without any noticeable degradation of filter response. All these methods drastically decrease the computation time by cutting it down constant times (e.g. to 0.06 seconds per 1MB image) while achieving very high PSNRpsilas over 45 dB. In addition to the computational advantages, our methods are straightforward to implement.
Keywords :
Gaussian processes; computational complexity; filtering theory; image sampling; series (mathematics); Gaussian range; O(1) bilateral filtering; Taylor series; arbitrary spatial filters; filter response degradation; integral histograms; linear filter decompositions; linear filters; polynomial range; spatial bilateral filters; Convolution; Filtering algorithms; Histograms; Kernel; Nonlinear filters; Polynomials; Runtime; Smoothing methods; Surface treatment; Taylor series;
Conference_Titel :
Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4244-2242-5
Electronic_ISBN :
1063-6919
DOI :
10.1109/CVPR.2008.4587843