基于L-DeepLabv3+的轻量化光学遥感图像道路提取  

Lightweight optical remote sensing image road extraction based on L-DeepLabv3+

作　　者：谢国波[1] 何林 林志毅[1] 张文亮 陈逸[2] XIE Guobo;HE Lin;LIN Zhiyi;ZHANG Wenliang;CHEN Yi(School of Computer Science,Guangdong University of Technology,Guangzhou 510006,China;International School of Information and Engineering,Dalian University of Technology,Dalian Liaoning 116024,China)

机构地区：[1]广东工业大学计算机学院,广州510006 [2]大连理工大学国际信息与软件学院,辽宁大连116024

出　　处：《激光杂志》2024年第3期111-117,共7页Laser Journal

基　　金：国家自然科学基金(No.62002070);广州市科技计划项目(No.201902020012)。

摘　　要：针对DeepLabv3+在进行光学遥感图像道路提取任务时,存在模型参数量大、细节提取效果差等问题,提出一种改进DeepLabv3+的轻量化道路提取模型L-DeepLabv3+。首先通过将主干网络替换为MobileNetv2来减少模型参数量;其次,在编码层中设计一个改进的空洞空间卷积池化金字塔模块。该模块通过嵌入一个通道空间并联注意力模块和YOLOF模块来增强模型特征表达能力,并且将普通卷积替换为深度可分离卷积进一步减少模型参数量;最后组合采用Dice_loss和Focal_loss作为损失函数来解决正负样本不均衡问题。实验结果表明:L-DeepLabv3+在DeepGlobe Road数据集上进行道路提取的交并比达到68.40%,像素准确率达到82.67%,且模型参数量仅为5.63 MB,FPS达到72.3,与其他模型相比具有明显提升,实现了模型精度与轻量化之间更好的平衡。To address the problems of large number of model parameters and poor detail extraction in DeepLabv3+for optical remote sensing image road extraction task,a light-weight road extraction model L-DeepLabv3+is proposed to improve DeepLabv3+.Firstly,the number of model parameters is reduced by replacing the backbone network with MobileNetv2;secondly,an improved void space convolutional pooling pyramid module is designed in the coding layer.This module enhances the model feature expression capability by embedding a channel space parallel attention module and YOLOF module,and replaces the normal convolution with deep separable convolution to further reduce the number of model parameters;Finally,Dice_loss and Focal_loss are combined as loss functions to solve the positive and negative sample imbalance problem.The experimental results show that L-DeepLabv3+achieves 68.40%intersection ratio and 82.67%pixel accuracy for road extraction on DeepGlobe Road dataset,and the number of model parameters is only 5.63 MB,and the FPS reaches 72.3,which is a significant improvement compared with other models,and achieves a better balance between model accuracy and light weight.

关 键 词：道路提取 L-DeepLabv3+ 光学遥感图像 语义分割 轻量化 

分 类 号：TN209[电子电信—物理电子学]