| Constant Time O (1) Bilateral Filtering |
| Citation: |
Porikli, F., "Constant Time O(1) Bilateral Filtering ", IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 2008 (IEEE Xplore) |
| Date: | July 2008 |
| MERL Contact: | Fatih Porikli |
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 approximations. 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 computational time by cutting it down constant times (e.g. to 0.06 seconds per 1MB image) while achieving very high PSNR's over 45dB. In addition to the computational advantages, our methods are straightforward to implement.
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