基于弱监督的遥感图像镶嵌质量盲评价  

Weak supervision based blind remote sensing image mosaic quality assessment

作　　者：潘林朋 谢凤英[1] 赵薇薇[2] 周颖 刘畅[1] 王艳[2] PAN Linpeng;XIE Fengying;ZHAO Weiwei;ZHOU Ying;LIU Chang;WANG Yan(School of Astronautics,Beihang University,Beijing 100191,China;Beijing Institute of Remote Sensing,Beijing 100192,China)

机构地区：[1]北京航空航天大学宇航学院,北京100191 [2]北京市遥感信息研究所,北京100192

出　　处：《北京航空航天大学学报》2023年第9期2518-2526,共9页Journal of Beijing University of Aeronautics and Astronautics

基　　金：国家重点研发计划(2019YFC1510905);国家自然科学基金(61871011)。

摘　　要：遥感图像镶嵌是遥感图像解译的一项重要研究内容,然而受成像时间、角度及地物纹理的影响,镶嵌图像经常会有颜色不一致、地物结构错位等情况。针对遥感图像镶嵌缝两侧出现的颜色差异、地物结构错位等质量问题,设计了双分支网络进行遥感图像镶嵌质量的盲评价,2个分支网络分别用于镶嵌缝两侧颜色差异评价和结构错位评价,综合2个网络的输出实现遥感图像镶嵌质量的综合评价。由于获得图像的质量真值需要耗费大量的人力物力,为了减少训练卷积网络所需要的数据量,提出了一种基于两阶段训练的弱监督学习策略,第1阶段在仿真的镶嵌数据集上以颜色差异量和结构错位量为客观真值对网络进行预训练,学习与质量评价有关的先验知识,第2阶段在有主观质量真值的数据集上进行微调。在建立的带有质量真值的仿真数据集和真实数据集上的实验结果表明:所提方法能够有效评价遥感图像镶嵌的质量,性能优于对比方法。A remote sensing image mosaic is an important research content of remote sensing image interpretation.However,affected by the imaging time,angle,and object texture,mosaic images often suffer inconsistent colors and structure dislocation.Aiming at the above quality problems,a double-branch network is designed to perform the blind assessment of the remote sensing image mosaic quality.The branch network are used to assess the color difference and structural dislocation respectively.Finally,the output of the branch networks is integrated to realize the comprehensive assessment.A weakly supervised learning technique based on two-stage training is proposed to lower the quantity of images in network training because it requires a lot of labor and material resources to determine the true score of the image quality.Firstly,to gain the previous knowledge associated with quality assessment,the network is initially pre-trained on the simulated mosaic dataset,which uses color change and structural dislocation as the objective quality score.Secondly,fine-tuning is performed on the dataset with subjective scores.Secondly,fine-tuning is performed on the dataset with subjective score.The experiment results on the established simulation dataset and authentic dataset show that the proposed method can effectively assess the quality of remote sensing image mosaic and outperforms the comparison algorithms.

关 键 词：遥感图像 镶嵌质量评价 弱监督学习 两阶段训练 颜色差异 结构错位 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]