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1.合肥工业大学 电子科学与应用物理学院, 安徽 合肥 230009
2.合肥工业大学 仪器科学与光电工程学院, 安徽 合肥 230009
3.合肥工业大学 特种显示技术国家工程实验室 现代显示技术省部共建国家重点实验室 光电技术研究院, 安徽 合肥 230009
[ "童正(1994-), 男, 安徽宿州人, 硕士研究生, 主要从事信息显示技术与器件等方向的研究。E-mail: tongzheng@mail.hfut.edu.cn" ]
[ "吕国强(1962-), 男, 浙江新昌人, 教授, 博士生导师, 1983年和1986年于浙江大学分别获得学士、硕士学位, 主要从事立体显示、液晶显示等方向的研究。E-mail:guoqianglv@hfut.edu.cn" ]
收稿日期:2018-07-05,
录用日期:2018-9-7,
纸质出版日期:2018-12
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童正, 吴磊, 赵晨, 等. 基于S曲线全局动态调光的改进算法[J]. 液晶与显示, 2018,33(12):1019-1025.
Zheng TONG, Lei WU, Chen ZHAO, et al. Improved algorithm based on S-curve global dynamic dimming[J]. Chinese journal of liquid crystals and displays, 2018, 33(12): 1019-1025.
童正, 吴磊, 赵晨, 等. 基于S曲线全局动态调光的改进算法[J]. 液晶与显示, 2018,33(12):1019-1025. DOI: 10.3788/YJYXS20183312.1019.
Zheng TONG, Lei WU, Chen ZHAO, et al. Improved algorithm based on S-curve global dynamic dimming[J]. Chinese journal of liquid crystals and displays, 2018, 33(12): 1019-1025. DOI: 10.3788/YJYXS20183312.1019.
S曲线全局动态调光算法可以降低LED液晶显示器的功耗,同时能够提高显示图像的静态对比度,但该算法会造成部分图像色彩失真和细节丢失。针对这一问题,本文提出一种图像细节层分离与视觉显著性理论相结合的S曲线改进算法。首先,将原始图像转换至HSV色彩空间进行亮度和色度分离;然后,在图像亮度分量上采用双边滤波得到图像的基础层与细节层,基础层采用S曲线进行动态范围拉伸,实现像素补偿,细节层则运用视觉显著性理论进行分区与权值增强,弥补由像素补偿带来的细节损失;最后,将处理后的各层图像转换至RGB空间显示。将本文算法的仿真结果与原S曲线算法的结果进行对比。结果显示,本文算法在维持原算法功耗降低和静态对比度提升水平不变的基础上,解决了原算法在部分图像中出现的色彩失真和细节丢失问题,提升了图像的视觉显示效果,同时本文算法的仿真结果具有更大的信息熵和平均梯度。
The S-curve global dynamic dimming algorithm can reduce the power consumption of the LED liquid crystal display
and at the same time improve the static contrast of the displayed image
but the algorithm will cause partial image color distortion and detail loss. To solve this problem
this paper proposes an improved S-curve algorithm combining image detail layer separation and visual saliency theory. Firstly
the original image is converted to the HSV color space for luminance and chrominance separation; then
the base layer and the detail layer of the image are obtained by bilateral filtering on the image luminance component
and the base layer is subjected to dynamic range stretching using the S curve to realize pixel compensation. The detail layer uses the visual saliency theory to perform partitioning and weight enhancement to compensate for the loss of detail caused by pixel compensation. Finally
the processed layers are converted to RGB space display. The simulation results of the algorithm are compared with the results of the original S-curve algorithm. The results show that the proposed algorithm solves the problem of color distortion and detail loss in some images based on the original algorithm's power consumption reduction and static contrast enhancement level
and improves the visual display effect of the image. The simulation results of the algorithm have greater information entropy and average gradient.
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