湖南大学学报（自然科学版）2025，Vol.52Issue(4)：44-56,13.DOI:10.16339/j.cnki.hdxbzkb.2025265
顾及小尺度目标特征重建的全局语义分割模型
Global Semantic Segmentation Model Considering Small-scale Target Feature Reconstruction
摘要
Abstract
To solve the problems of insufficient understanding and fuzzy feature boundary segmentation of multi-target categories small-scale feature semantic information in aerial remote sensing images in complex background,this paper designs a segmentation model that integrates the features of the backbone network information and classifies and reconstructs the features to improve the segmentation effect.The model takes Swin-Transformer as the coding structure and utilizes its ability to understand global semantic information for feature extraction.The segmentation of small-scale target features is refined by the designed information grouping reconstruction convolution(IGRM)and channel classification reconstruction convolution(CRRM),which classify and reconstruct the extracted features by the amount of information.Finally,by integrating the up-sampling and down-sampling connections,the reconstructed features are fused with the features extracted by the encoder to form a multi-scale feature aggregation block to output the segmentation results.The refined reconstruction of small-scale target features is realized in multi-target scenarios with complex backgrounds,and high-quality segmentation maps are generated to improve the segmentation accuracy.Experimental results on the ISPRS Potsdam and ISPRS Vaihingen datasets show that the average intersection and merger ratio(mIoU)is 87.15%and 82.93%,respectively,and the overall accuracy(OA)is 91.53%and 91.4%,respectively.To verify the generalization ability of the model for small-scale target feature extraction in multi-target categories,this paper also designs a comparative experiment for the category of carts in complex backgrounds.The experimental results show that the mIoU on the UAVid dataset reaches 67.86%.关键词
航空遥感/语义分割/信息聚合重构模块/通道区分重构模块/整合上采样Key words
aerial remoteness/semantic segmentation/information grouping reconstruction module(IGRM)/channel classification reconstruction module(CRRM)/integrated up-sampling分类
计算机与自动化引用本文复制引用
吴小所,乔煜栋,贺成龙,刘小明,闫浩文..顾及小尺度目标特征重建的全局语义分割模型[J].湖南大学学报（自然科学版）,2025,52(4):44-56,13.基金项目
国家重点研发计划资助项目(2022YFB3903604),National Key Research and Development Program of China(2022YFB3903604) （2022YFB3903604）
甘肃省自然科学基金资助项目(21JR7RA310),Gansu Provincial Natural Science Foundation(21JR7RA310) （21JR7RA310）
兰州交通大学青年科学基金资助项目(2021029),Lanzhou Jiaotong University Youth Science Foundation(2021029) （2021029）
