ACM Transactions on Graphics · 2002 · 983 citations · 22 references
ArtsComputer ScienceComputer VisionDigital ImagingRenderingDigital Image ProcessingHigh-dynamic-range ImagingImage EnhancementImage FilteringImage ProcessingImage RestorationBilateral FilteringContrast Enhancement FiltersEdge-preserving FilteringHigh Dynamic Range (Hdr) ImagingHigh Dynamic Range RenderingImage Detail EnhancementInfluence FunctionLinear Approximation
We present a new technique for the display of high-dynamic-range images, which reduces the contrast while preserving detail. It is based on a two-scale decomposition of the image into a base layer, encoding large-scale variations, and a detail layer. Only the base layer has its contrast reduced, thereby preserving detail. The base layer is obtained using an edge-preserving filter called the bilateral filter. This is a non-linear filter, where the weight of each pixel is computed using a Gaussian in the spatial domain multiplied by an influence function in the intensity domain that decreases the weight of pixels with large intensity differences. We express bilateral filtering in the framework of robust statistics and show how it relates to anisotropic diffusion. We then accelerate bilateral filtering by using a piecewise-linear approximation in the intensity domain and appropriate subsampling. This results in a speed-up of two orders of magnitude. The method is fast and requires no parameter setting.
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Robust Statistics: The Approach Based on Influence Functions
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