Real-time Image Enhancement Using Edge-Optimized a-trous Wavelets

Edge-avoiding a-trous wavelets (EAAW) offer an elegant and simple way for advanced real-time image smoothing and contrast enhancement. Based on the bilateral filter, edge-avoiding wavelets perform multi-resolution analysis. By optimizing the edge weights to match the edge shape at every scale contrast enhancement can be obtained without the typically encountered artifacts of halos or gradient reversals. We demonstrate examples of real-time aging, as well as smooth reconstruction of noisy Monte Carlo simulations. In addition, an edge-avoiding wavelet framework is presented to emphasize monocular depth cues in 2D images captured with a stereo camera. We demonstrate that these enhanced depth cues can aid the human in 3D search tasks on traditional monitors without degenerating the image.