A gentle introduction to bilateral filtering and its applications
ACM SIGGRAPH 2007 courses
A gentle introduction to bilateral filtering and its applications
ACM SIGGRAPH 2008 classes
ACM SIGGRAPH 2009 papers
Hyperspectral image enhancement with vector bilateral filtering
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Automatic skin enhancement with visible and near-infrared image fusion
Proceedings of the international conference on Multimedia
High quality video acquisition and segmentation using alternate flashing system
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Pansharpening of high and medium resolution satellite images using bilateral filtering
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Visual enhancement of old documents with hyperspectral imaging
Pattern Recognition
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
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We present a technique for enhancing underexposed visible-spectrum video by fusing it with simultaneously captured video from sensors in nonvisible spectra, such as Short Wave IR or Near IR. Although IR sensors can accurately capture video in low-light and night-vision applications, they lack the color and relative luminances of visible-spectrum sensors. RGB sensors do capture color and correct relative luminances, but are underexposed, noisy, and lack fine features due to short video exposure times. Our enhanced fusion output is a reconstruction of the RGB input assisted by the IR data, not an incorporation of elements imaged only in IR. With a temporal noise reduction, we first remove shot noise and increase the color accuracy of the RGB footage. The IR video is then normalized to ensure cross-spectral compatibility with the visible-spectrum video using ratio images. To aid fusion, we decompose the video sources with edge-preserving filters. We introduce a multispectral version of the bilateral filter called the "dual bilateral" that robustly decomposes the RGB video. It utilizes the less-noisy IR for edge detection but also preserves strong visible-spectrum edges not in the IR. We fuse the RGB low frequencies, the IR texture details, and the dual bilateral edges into a noise-reduced video with sharp details, correct chrominances, and natural relative luminances