基于像素梯度自适应迭代中值滤波器的图像脉冲噪声抑制算法  

Pixel gradient-based adaptive iterative median filter for image impulse noise removal

作　　者：金祥博 王跃明[1,2] JIN Xiang-Bo;WANG Yue-Ming(Key Laboratory of Space Active Opto-Electronics Technology,Shanghai Institute of Technical Physics,Chinese Academy of Sciences,Shanghai 200083,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院上海技术物理研究所空间主动光电技术重点实验室,上海200083 [2]中国科学院大学,北京100049

出　　处：《红外与毫米波学报》2024年第3期421-434,共14页Journal of Infrared and Millimeter Waves

基　　金：the National Civil Aerospace Project of China(D040102)。

摘　　要：图像脉冲噪声移除是获得高质量图像的关键。本文通过热红外相机成像原理研究,提出了一种基于像素梯度自适应迭代中值滤波器的图像脉冲噪声抑制算法。首先,根据相机的调制传递函数计算获取原始图像的最大像素梯度,继而建立相应的像素梯度集合。然后,计算原始图像与对应像素梯度滤波图像的梯度权重均方根误差集合,并将该集合高斯分布的最大值对应的像素梯度确定为最佳像素梯度。最后,根据图像中脉冲噪声的密度和复杂度,确定所提滤波器的自适应窗口大小和迭代次数。大量实验结果表明,所提滤波器对移除8位、16位的单通道脉冲噪声图像展现出良好的鲁棒性。与其他先进方法相比,该方法可以实时移除真实热红外相机采集图像中低密度的随机值脉冲噪声和SAPN,并实现噪声抑制过程中99.5%以上的原始像素不会遭受破坏。除此之外,针对高密度SAPN抑制,该方法获得了具有竞争力的结果,与运行时间较快的滤 波方法相比表现出较好的 PSNR和 SSIM,与 PSNR和 SSIM较优秀的去噪方法相比表现出较快的运行时间。对于极限 SAPN(99%)破坏的图像,也能够恢复有意义的图像细节。Image impulse noise removal is essential for obtaining high-quality images.A novel pixel gradientsbased adaptive iterative median filter is proposed to remove image impulse noise by utilizing the principles of ther⁃mal infrared camera imaging.Firstly,the maximum pixel gradient of the original image is computed based on the camera's modulation transfer function(MTF),and a corresponding set of pixel gradients is established.Subse⁃quently,the gradient weight root-mean-square error(GWRMSE)set of the original image and the corresponding pixel gradient filtered image is computed,and the optimal pixel gradient is determined as the one corresponding to the maximum value of Gaussian distribution of the GWRMSE set.Finally,the adaptive window size and number of iterations for the proposed filter are determined according to the density and complexity of the impulse noise in the image.Extensive experimental results demonstrate that the proposed filter exhibits excellent robustness in re⁃moving 8-bit and 16-bit single-channel impulse noise images.In comparison with other state-of-the-art methods,the proposed method can remove low-density random-valued impulse noise(RVIN)and salt-and-pepper noise(SAPN)in real thermal infrared camera-acquired images in real-time while preserving more than 99.5%of origi⁃nal pixels during the noise removal process.Additionally,for high-density SAPN removal,the proposed method achieves competitive results,demonstrating better peak signal-to-noise ratio(PSNR)and structural similarity in⁃dex(SSIM)in comparison with filtering methods of faster running time and faster execution time in comparison with denoising methods of superior PSNR and SSIM.Moreover,it can recover meaningful image details even for images severely damaged by extreme SAPN(99%).

关 键 词：图像去噪 自适应迭代中值滤波器 像素梯度 调制传递函数 脉冲噪声 

分 类 号：TN215[电子电信—物理电子学] TP51.1[自动化与计算机技术]