基于特征加权融合的红外图像增强方法
Infrared image enhancement method based on feature-weighted fusion
田静1
作者信息
摘要
红外图像增强可以改善图像中的细节和对比度,使得目标在图像中更加清晰可见,对红外图像的目标检测和识别任务具有重要意义.为此,提出一种基于特征加权融合的红外图像增强方法.首先分析红外图像对比度和边缘细节,结合光谱特征融合方法进行红外图像的降噪预处理.提取降噪后红外图像的区域梯度特征后,加权融合所提取的具体图像特征,利用Retinex算法对加权融合的红外图像特征进行色调映射,实现最终的红外图像增强处理.结果显示,本方法MSE为0.603％,PSNR为49.11 dB,SSIM为0.988.由此证明,采用该方法可以实现红外图像的增强处理,具有一定应用价值.
Abstract
Infrared image enhancement can improve the details and contrast in the image,and make the target more clearly visible in the image,which is of great significance to the task of target detection and recognition in infra-red images.Therefore,an infrared image enhancement method based on feature weighted fusion is proposed.Firstly,the contrast and edge details of infrared image are analyzed,and the denoising pretreatment of infrared image is carried out by combining spectral feature fusion method.After extracting the regional gradient features of the denoised infrared image,the extracted specific image features are weighted and fused,and the weighted and fused infrared image fea-tures are tone mapped by Retinex algorithm to realize the final infrared image enhancement processing.Taking mean square error,peak signal-to-noise ratio and structural similarity as experimental test indicators,the results show that the MSE,PSNR and SSIM of this method are 0.603％,49.11 dB and 0.988 respectively.It is proved that this meth-od can enhance the infrared image and has certain application value.
关键词
图像增强/红外图像/稀疏表示/特征加权融合/光谱特征Key words
image enhancement/infrared image/sparse representation/feature-weighted fusion/spectral fea-tures引用本文复制引用
基金项目
辽宁省公安大数据智能应用重点实验室项目(2022JH13/10200047)
出版年
2024
NETL
NSTL
万方数据