SiameseDenseU-Net-based Semantic Segmentation of Urban Remote Sensing Images

Rongsheng Dong, Lulu Bai and Fengying Li

Mathematical Problems in Engineering, 2020, vol. 2020, 1-14

Abstract:

Boundary pixel blur and category imbalance are common problems that occur during semantic segmentation of urban remote sensing images. Inspired by DenseU-Net, this paper proposes a new end-to-end network—SiameseDenseU-Net. First, the network simultaneously uses both true orthophoto (TOP) images and their corresponding normalized digital surface model (nDSM) as the input of the network structure. The deep image features are extracted in parallel by downsampling blocks. Information such as shallow textures and high-level abstract semantic features are fused throughout the connected channels. The features extracted by the two parallel processing chains are then fused. Finally, a softmax layer is used to perform prediction to generate dense label maps. Experiments on the Vaihingen dataset show that SiameseDenseU-Net improves the F 1-score by 8.2% and 7.63% compared with the Hourglass-ShapeNetwork (HSN) model and with the U-Net model. Regarding the boundary pixels, when using the same focus loss function based on median frequency balance weighting, compared with the original DenseU-Net, the small-target “car” category F 1-score of SiameseDenseU-Net improved by 0.92%. The overall accuracy and the average F 1-score also improved to varying degrees. The proposed SiameseDenseU-Net is better at identifying small-target categories and boundary pixels, and it is numerically and visually superior to the contrast model.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2020/1515630.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2020/1515630.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1515630

DOI: 10.1155/2020/1515630

Access Statistics for this article

More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().