论文标题
噪音吸引质地的低光增强
Noise-Aware Texture-Preserving Low-Light Enhancement
论文作者
论文摘要
在这项工作中提出了一种基于噪声感知纹理纹理的视角模型的简单有效的低光图像增强方法。这种称为Natle的新方法试图通过低复杂的解决方案在降噪和自然纹理保护之间取得平衡。它的成本功能包括估计的零件平滑照明图和无噪声纹理的反射图。之后，调整照明以形成增强的图像以及反射率图。在常见的低光图像增强数据集上进行了广泛的实验，以证明NATLE的出色性能。
A simple and effective low-light image enhancement method based on a noise-aware texture-preserving retinex model is proposed in this work. The new method, called NATLE, attempts to strike a balance between noise removal and natural texture preservation through a low-complexity solution. Its cost function includes an estimated piece-wise smooth illumination map and a noise-free texture-preserving reflectance map. Afterwards, illumination is adjusted to form the enhanced image together with the reflectance map. Extensive experiments are conducted on common low-light image enhancement datasets to demonstrate the superior performance of NATLE.
