On the Role of Shaped-Noise Visibility for Post-Compression Image Enhancement
On the Role of Shaped-Noise Visibility for Post-Compression Image Enhancement
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关于形状噪声可见性在压缩后图像增强中的作用
DOI：
10.1007/978-3-319-99834-3_26
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
and G. Ohashi
中科院分区：
文献类型：
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作者：
K. Kawai;D. M. Chandler;and G. Ohashi
数字图像要经过不可逆的压缩才能传输，这一过程会引起可见的、经常令人讨厌的失真。压缩后增强算法试图减少这些扭曲对视觉的影响。一种这样的增强技术，专门为纹理设计，采用感知形状的噪声模式。虽然这种技术非常有效，但是模式的对比必须适当地缩放，因此需要一种能够自动预测这些缩放因子的算法。为了帮助实现这样的预测，我们研究了具有更高对比度检测阈值（CTs）的模式[即需要更高对比度才能刚刚可见的模式]是否也需要更高的对比度缩放因子（CSs）来进行适当的增强。我们在本研究中测量了ct，并将其与我们之前研究中测量的CSs进行了比较。我们的研究结果支持低CT意味着低CS的假设，反之亦然，但仅适用于那些能显著改善视觉质量的模式。
Digital images undergo irreversible compression to enable transmission, a process which induces visible and often annoying distortions. Post-compression enhancement algorithms attempt reduce the visual impacts of these distortions. One such enhancement technique, designed specifically for textures, employs perceptually shaped noise patterns. Although this technique is quite effective, the contrasts of the patterns must be properly scaled, thus necessitating an algorithm that can automatically predict these scaling factors. To help enable such a prediction, we investigated whether patterns which have higher contrast detection thresholds (CTs) [i.e., patterns which require more contrast to be just-visible] also require higher contrast scaling factors (CSs) for proper enhancement. We measured CTs in the current study and compared them with CSs measured in our previous study. Our results support the hypothesis that low CT implies low CS, and vice-versa, but only for those patterns which could markedly improve the visual quality.