School of Electronic Engineering, Soongsil University, Seoul 06978, Korea.
Sensors (Basel). 2019 Feb 25;19(4):969. doi: 10.3390/s19040969.
This paper introduces an adaptive image rendering using a parametric nonlinear mapping-function-based on the retinex model in a low-light source. For this study, only a luminance channel was used to estimate the reflectance component of an observed low-light image, therefore halo artifacts coming from the use of the multiple center/surround Gaussian filters were reduced. A new nonlinear mapping function that incorporates the statistics of the luminance and the estimated reflectance in the reconstruction process is proposed. In addition, a new method to determine the gain and offset of the mapping function is addressed to adaptively control the contrast ratio. Finally, the relationship between the estimated luminance and the reconstructed luminance is used to reconstruct the chrominance channels. The experimental results demonstrate that the proposed method leads to the promised subjective and objective improvements over state-of-the-art, scale-based retinex methods.
本文提出了一种基于低光源下的视网膜模型的参数非线性映射函数的自适应图像渲染方法。在这项研究中，仅使用亮度通道来估计观察到的低光图像的反射分量，因此减少了由于使用多个中心/环绕高斯滤波器而产生的晕影伪影。提出了一种新的非线性映射函数，该函数在重建过程中结合了亮度和估计反射率的统计信息。此外，还提出了一种新的方法来确定映射函数的增益和偏移量，以自适应地控制对比度比。最后，使用估计的亮度和重建的亮度之间的关系来重建色度通道。实验结果表明，与基于尺度的视网膜方法相比，所提出的方法在主观和客观上都有了预期的改进。
