Building change detection by W-shape resunet++ network with triple attention mechanism

A. Eftekhari, F. Samadzadegan, F. Dadrass javan

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Abstract

Building change detection in high resolution remote sensing images is one of the most important and applied topics in urban management and urban planning. Different environmental illumination conditions and registration problem are the most error resource in the bitemporal images that will cause pseudochanges in results. On the other hand, the use of deep learning technologies especially convolutional neural networks (CNNs) has been successful and considered, but usually causes the loss of shape and detail at the edges. Accordingly, we propose a W-shape ResUnet++ network in which images with different environmental conditions enter the network independently. ResUnet++ is a network with residual blocks, triple attention blocks and Atrous Spatial Pyramidal Pooling. ResUnet++ is used on both sides of the network to extract deeper and discriminator features. This improves the channel and spatial inter-dependencies, while at the same time reducing the computational cost. After that, the Euclidean distance between the features is computed and the deconvolution is done. Also, a dual loss function is designed that used the weighted binary cross entropy to solve the unbalance between the changed and unchanged data in change detection training data and in the second part, we used the mask–boundary consistency constraints that the condition of converging the edges of the training data and the predicted edge in the loss function has been added. We implemented the proposed method on two remote sensing datasets and then compared the results with state-of-the-art methods. The F1 score improved 1.52 % and 4.22 % by using the proposed model in the first and second dataset, respectively.
Original languageEnglish
Title of host publicationThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
EditorsM.R. Delavar, R. Ali Abbaspour, S. Farzaneh
Place of PublicationTehran
PublisherCopernicus
Pages23-29
VolumeXLVIII-4/W2-2022
DOIs
Publication statusPublished - 12 Jan 2023
EventGeoSpatial Conference 2022 - virtual, Tehran, Iran, Islamic Republic of
Duration: 19 Feb 202322 Feb 2023
https://www.sru.ac.ir/en/4860-2/

Publication series

NameThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences

Conference

ConferenceGeoSpatial Conference 2022
Country/TerritoryIran, Islamic Republic of
CityTehran
Period19/02/2322/02/23
OtherJoint 6th SMPR and 4th GIResearch Conferences
Internet address

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