基于双线性滤波器的安防相机低照度去噪研究

针对安防监控摄像机在夜间拍摄时易产生噪声，以及所使用的图像去噪方法易产生图像边缘特征退化的问题，提出了一种基于图像像素值差的监控摄像机低照度去噪方法。通过计算像素值差，再下采样得到图像金字塔，以获得整体和局部像素值差的索引，由此设计了一种适用于低照度的去噪卷积核，以增加噪声对中间像素值的影响，实现低照度环境下图像噪点的消除并保留其边缘特征。实验表明，该方法在低照度场景实际应用中既去除了图像的噪点，又保留了边缘信息。与基于小波变换的算法相比，该方法明显提升了图像的主观评价质量，并在Imatest信噪比测试中提升了图像的亮度信噪比。

Research on a low illuminance denoising method based on bilateral filter for security cameras

Denoising has long posed a significant challenge for security cameras, even with the denoising algorithms, on which modern security cameras heavily rely. These algorithms often lead to a degradation of image edges, especially in low illuminance conditions. To tackle this problem, a low illuminance image denoising algorithm is proposed, which aims to minimize the loss of edge information while reducing noise based on pixel value deviations. In light of the human visual system, we construct an image pyramid from the pixel values, allowing us to analyze local and global pixel value differences and mitigate the noisy influence on pixels of medium value. Experimental results show that the proposed algorithm removes the noise signal in nighttime road images, preserves edge details, enhances the overall image quality compared to the classic wavelet denoising algorithm, and improves the signal-to-noise ratio according to the Imatest SNR test.