LCIS: a boundary hierarchy for detail-preserving contrast reduction
LCIS: a boundary hierarchy for detail-preserving contrast reduction
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DOI：
10.1145/311535.311544
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发表时间：
1999-07
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通讯作者：
J. Tumblin;Greg Turk
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文献类型：
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作者：
J. Tumblin;Greg Turk
高对比度场景在低对比度显示器上难以描绘，且会丢失重要的精细细节和纹理。熟练的艺术家通过使用场景边界和阴影的层次结构，按照从粗到细的顺序绘制场景内容来保留这些细节。我们使用一种新的低曲率图像简化器（LCIS）的多个实例构建了一个类似的层次结构，这是一个受各向异性扩散启发的偏微分方程。每个LCIS将场景简化为许多由尖锐梯度不连续边界限定的平滑区域，并且为每个LCIS选择的单个参数K控制区域大小和边界复杂性。通过选择几个K值（K1 > K2 > K3……），LCIS生成一组逐渐简化的图像，并且图像差异形成了一个重要性逐渐增加的细节、边界和大特征的层次结构。我们通过仅压缩大特征，然后添加回所有小细节，从这个层次结构中构建一个高细节、低对比度的显示图像。与小波、滤波器组或图像金字塔等线性滤波器层次结构不同，LCIS层次结构不会在场景边界上平滑，避免了先前对比度降低方法和一些色调再现算子常见的“光晕”伪影。我们在几个示例图像上展示了LCIS的有效性。CR分类描述符：I.3.3 [计算机图形学]：图像生成 - 显示算法；I.4.1 [图像处理和计算机视觉]：增强 - 数字化和图像采集
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. CR Descriptors: I.3.3 [Computer Graphics]: Picture/image generation Display algorithms; I.4.1 [Image Processing and Computer Vision]: Enhancement -Digitization and Image Capture