“LCIS: a boundary hierarchy for detail-preserving contrast reduction” by Tumblin and Turk

  • ©Jack Tumblin and Greg Turk




    LCIS: a boundary hierarchy for detail-preserving contrast reduction



    High contrast scenes are difficult to depict on low contrast displays without loss of important fine details and textures. Skilled artists preserve these details by drawing scene contents in coarseto-fine order using a hierarchy of scene boundaries and shadings. We build a similar hierarchy using multiple instances of a new low curvature image simplifier (LCIS), a partial differential equation inspired by anisotropic diffusion. Each LCIS reduces the scene to many smooth regions that are bounded by sharp gradient discontinuities, and a single parameter K chosen for each LCIS controls region size and boundary complexity. With a few chosen K values (K1 > K2 > K3:::) LCIS makes a set of progressively simpler images, and image differences form a hierarchy of increasingly important details, boundaries and large features. We construct a high detail, low contrast display image from this hierarchy by compressing only the large features, then adding back all small details. Unlike linear filter hierarchies such as wavelets, filter banks, or image pyramids, LCIS hierarchies do not smooth across scene boundaries, avoiding “halo” artifacts common to previous contrast reducing methods and some tone reproduction operators. We demonstrate LCIS effectiveness on several example images.


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