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在分析国内电力行业应用需求的基础上,对无人值守变电站远程视频监控系统中的图像增强算法做了深入研究。根据人类视网膜对信号的处理方式,提出了基于人类视网膜处理流程的图像增强算法,该算法首先通过多尺度闭运算操作对原始图像中的噪声进行抑制和消除,然后使用Bayer模式的彩色滤波阵列对图像进行采样操作并模拟视网膜进行两次非线性处理,最后通过插值算法恢复图像的全彩色信息。实验证明,基于视网膜模型的增强算法能够显著提高暗区域图像的信息量,在无人值守变电站远程视频监控系统中有很好的使用及推广价值。
Based on the analysis of the application requirements of the domestic electric power industry, the image enhancement algorithm in the remote video surveillance system of unattended substations is studied in depth. According to human retinal signal processing approach, a human-based retina processing image enhancement algorithm is proposed. Firstly, the noise in the original image is suppressed and eliminated by multi-scale closed-loop operation. Then, the Bayer pattern color filter array Image sampling operation and simulate the retina twice nonlinear processing, and finally by interpolation algorithm to restore the image full color information. Experiments show that the enhancement algorithm based on retina model can significantly improve the amount of information in dark area images and is well used and popularized in unmanned substation remote video surveillance system.