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基于改进CNN网络模型的红外图像非均匀校正算法

Infrared Image Non-uniform Correction Algorithm Based on Improved CNN Network Model
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摘要 针对现有红外图像非均匀校正算法存在的校正效果差等问题,设计了一种基于改进CNN网络模型的校正算法。对采集到的多幅红外图像进行配准和降噪处理,形成二维红外图像数据集;构建CNN模型并为卷积层选择适合的卷积核、步长,为抑制卷积层存在的梯度弥散等情况并且进一步提升二维红外图像数据的训练能力,利用残差块对卷积层进行优化和改进,最后基于最小均方算法对融合后的红外图像的边缘进行校正。实验结果显示:提出的非均匀校正算法,能够有效改善图像的亮度不均和噪点等问题,纠正后的图像5个区域的粗糙度均值和均方根均值分别为1.779和0.643,相对于原图有明显改善,校正效果也优于两种传统算法。 Aiming at the problems of the existing non-uniform infrared image correction algorithms,a correction algorithm based on the improved CNN network model is designed.Firstly,the collected infrared images are registered and denoised to form a two-dimensional infrared image dataset as the input item of model.The CNN model is constructed and suitable convolution kernel and step size is selected for the convolution layer.In order to suppress the gradient dispersion of the convolution layer and further improve the training ability of two-dimensional infrared image data,residual blocks are used to optimize and improve the convolution layer.Finally,the edge of the fused infrared image is corrected based on the least mean square algorithm.The experimental results show that the proposed non-uniform correction algorithm can effectively improve the problems of uneven brightness and noise in the image,and the mean roughness and mean root mean value of the 5 regions of the corrected image are 1.779 and 0.643,respectively,which are significantly improved compared with the original image,and the correction effect is better than the two traditional algorithms.
作者 高倩 单大甫 李颖 蒋宇豪 GAO Qian;SHAN Dafu;LI Ying;JIANG Yuhao(Department of Journalism and Communication,Anhui Vocational College of Press and Publication,Hefei 230601,China;Anhui Qixin Mingzhi Technology Co.,Ltd.,Hefei 230093,China;Wuhu Media Center,Wuhu Anhui 241000,China;School of Mechanical Electronic and Control Engineering,Beijing Jiaotong University,Beijing 100044,China)
出处 《佳木斯大学学报(自然科学版)》 CAS 2024年第11期34-36,95,共4页 Journal of Jiamusi University:Natural Science Edition
基金 2022年度安徽省高校科研项目(2022AH053001) 2022年度安徽省教学研究项目(2022jyxm674)。
关键词 改进CNN 红外图像 非均匀校正 卷积核 粗糙度 improved CNN infrared image non-uniform correction convolution kernel roughness
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