中南民族大学学报（自然科学版）2026，Vol.45Issue(4)：505-513,9.DOI:10.20056/j.cnki.ZNMDZK.20250847
基于随机置换的红外图像超分辨率Transformer
Transformer of infrared image super-resolution based on random permutation
摘要
Abstract
Infrared image super-resolution has wide applications.Currently,the Visual Transformer has shown great potential in improving the performance of image super-resolution,but how to effectively balance system complexity has attracted the interest of many researchers.A random permutation based Transformer for infrared image super-resolution is proposed,which achieves further improvement in image reconstruction performance while controlling system complexity well.Specifically,a window self-attention module combining random permutation is designed to replace the original Swin Transformer's shifted window self-attention module,effectively improving the learning ability of global dependency relationships of window self-attention through random permutation operations in the spatial dimension of the feature map.Experimental comparison results based on multiple public infrared image datasets validate the effectiveness of this method.关键词
红外图像超分辨率/视觉Transformer/全局建模/随机置换Key words
infrared image super-resolution/Visual Transformer/global modeling ability/random permutation分类
信息技术与安全科学引用本文复制引用
熊承义,何缘,高志荣,曹雨轩,李明月,王薇..基于随机置换的红外图像超分辨率Transformer[J].中南民族大学学报（自然科学版）,2026,45(4):505-513,9.基金项目
多谱信息处理技术国家重点实验室基金资助项目(6142113210303) （6142113210303）
中央高校基本科研业务专项资金资助项目(CZY21013) （CZY21013）
