红外技术2026，Vol.48Issue(1)：18-26,9.
基于融合高频信息的红外图像超分辨率算法
Super-resolution Algorithm of Infrared Imaging Based on Fusing High-Frequency Information
摘要
Abstract
To address the problems of insufficient temperature measurement accuracy and low resolution of current thermal imaging cameras,a temperature super-resolution model with an enhanced detail high-frequency component is developed by integrating a high-frequency filter block.The model first extracts the shallow features of a feature map through a convolutional layer.Second,a high-frequency filter block is introduced to highlight the high-frequency information,and jump joins are used to combine the raw data with high-frequency information.Finally,the temperature data are upsampled via convolution and pixel rearrangement,thus improving the resolution.This experiment is conducted on a self-constructed dataset,and the experimental results show that the enhanced detail high-frequency component model outperforms the fast super-resolution convolutional neural network and enhanced deep super-resolution network models.关键词
温度修正/分辨率/卷积神经网络/高频信息块/像素重排Key words
temperature correction/resolution/convolutional neural network/high-frequency information block/pixel rearrangement分类
信息技术与安全科学引用本文复制引用
魏永超,刘倩倩,朱泓超,朱姿翰..基于融合高频信息的红外图像超分辨率算法[J].红外技术,2026,48(1):18-26,9.基金项目
西藏科技厅重点研发计划(XZ202101ZY0017G) （XZ202101ZY0017G）
四川省科技厅重点研发项目(2022YFG0356) （2022YFG0356）
中国民用航空飞行学院科研基金(J2020-040,CJ2020-01). （J2020-040,CJ2020-01）
