计算机工程与应用2017，Vol.53Issue(20)：180-186,7.DOI:10.3778/j.issn.1002-8331.1702-0105
一种改进的基于深度学习的遥感影像拼接方法
Modified approach to remote sensing image mosaic based on deep learning
摘要
Abstract
Image registration and coordinate transformation are two important processes of remote sensing image mosaic in different backgrounds,which are studied respectively in this paper.Focused on the image registration,a method based on hierarchical convolutional features is proposed.This method adaptively obtains image features from CNN(Convolu-tional Neural Networks)and then sends the features derived from different images in different depth to CF(Correlation Filter)to compute the similarity between them.Therefore the locations of the feature points are computed with consider-ing the different depth hierarchical convolutional features.In order to simplify the coordinate transform method,the cross points method is proposed.According to the feature points location from the image registration,the transform parameters can be computed.Then the remote sensing images can be mosaicked by converting all pixels from one image to another. The experimental results show the effectiveness and robustness of the proposed method by comparing to traditional mosaic method based on SIFT(Scale Invariant Feature Transform).关键词
卷积神经网络(CNN)/图像配准/十字点集/遥感影像拼接Key words
Convolutional Neural Networks(CNN)/image registration/cross points/remote sensing image mosaic分类
信息技术与安全科学引用本文复制引用
雒培磊,李国庆,曾怡..一种改进的基于深度学习的遥感影像拼接方法[J].计算机工程与应用,2017,53(20):180-186,7.基金项目
海南省重大科技计划项目(No.ZDKJ2016021) （No.ZDKJ2016021）
国家重点研发计划(No.2016YFB0501504) （No.2016YFB0501504）
DBAR中科院"一带一路"专项项目 （）
北京市自然科学基金(No.6164038). （No.6164038）
