  The bilateral filter has diverse applications in image processing, computer
vision, and computational photography. In particular, this non-linear filter is
quite effective in denoising images corrupted with additive Gaussian noise. The
filter, however, is known to perform poorly at large noise levels. Several
adaptations of the filter have been proposed in the literature to address this
shortcoming, but often at an added computational cost. In this paper, we report
a simple yet effective modification that improves the denoising performance of
the bilateral filter at almost no additional cost. We provide visual and
quantitative results on standard test images which show that this improvement
is significant both visually and in terms of PSNR and SSIM (often as large as 5
dB). We also demonstrate how the proposed filtering can be implemented at
reduced complexity by adapting a recent idea for fast bilateral filtering.
