IEEE Trans Image Process. 2017 Feb;26(2):982-993. doi: 10.1109/TIP.2016.2639450. Epub 2016 Dec 14.
When one captures images in low-light conditions, the images often suffer from low visibility. Besides degrading the visual aesthetics of images, this poor quality may also significantly degenerate the performance of many computer vision and multimedia algorithms that are primarily designed for high-quality inputs. In this paper, we propose a simple yet effective low-light image enhancement (LIME) method. More concretely, the illumination of each pixel is first estimated individually by finding the maximum value in R, G, and B channels. Furthermore, we refine the initial illumination map by imposing a structure prior on it, as the final illumination map. Having the well-constructed illumination map, the enhancement can be achieved accordingly. Experiments on a number of challenging low-light images are present to reveal the efficacy of our LIME and show its superiority over several state-of-the-arts in terms of enhancement quality and efficiency.
当在低光照条件下捕捉图像时，图像往往会出现可见度低的问题。除了降低图像的视觉美感外，这种低质量还可能显著降低许多主要为高质量输入设计的计算机视觉和多媒体算法的性能。在本文中，我们提出了一种简单而有效的低光照图像增强（LIME）方法。更具体地说，首先通过找到R、G和B通道中的最大值来单独估计每个像素的光照。此外，我们通过在其上施加结构先验来细化初始光照图，作为最终的光照图。有了构建良好的光照图，就可以相应地实现增强。对一些具有挑战性的低光照图像进行了实验，以揭示我们的LIME的有效性，并在增强质量和效率方面显示其优于几种现有技术。
