Marine cage aquaculture information extraction based on deep edge spectral U-Net

Ke Li’na; Zhai Yuning; Fan Jianchao

doi:10.12284/hyxb2022026

Volume 44 Issue 2

Feb. 2022

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Ke Li’na，Zhai Yuning，Fan Jianchao. Marine cage aquaculture information extraction based on deep edge spectral U-Net[J]. Haiyang Xuebao，2022, 44(2)：132–142 doi: 10.12284/hyxb2022026

Citation:

Ke Li’na，Zhai Yuning，Fan Jianchao. Marine cage aquaculture information extraction based on deep edge spectral U-Net[J]. Haiyang Xuebao，2022, 44(2)：132–142 doi: 10.12284/hyxb2022026

Citation:

Ke Li’na，Zhai Yuning，Fan Jianchao. Marine cage aquaculture information extraction based on deep edge spectral U-Net[J]. Haiyang Xuebao，2022, 44(2)：132–142 doi: 10.12284/hyxb2022026

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Marine cage aquaculture information extraction based on deep edge spectral U-Net

doi: 10.12284/hyxb2022026

Ke Li’na^1
,,
Zhai Yuning^{1, 2},
Fan Jianchao^{2
,
,}

1.
School of Geography, Liaoning Normal University, Dalian 116029, China
2.
Department of Marine Remote Sensing Technology, National Marine Environmental Monitoring Center, Dalian 116023, China

Received Date: 2021-06-05
Rev Recd Date: 2021-09-01

Available Online: 2021-10-25

Publish Date: 2022-02-01

Abstract

Abstract

Cage aquaculture is one of the most important types of mariculture. The spectral characteristics of offshore cage aquaculture are greatly affected by the coastal vegetation and water body, so it is easy to cause noise problems. The new type of deep-sea cage aquaculture target is far from the shore, but the sea surface frame part of the aquaculture target is small, which has high spectral similarity with the natural water, and is difficult to extract. In this paper, deep edge spectral U-Net (DES-Unet) model is proposed to extract aquaculture information of two types of cage aquaculture. In this model, Canny operator bilateral filtering algorithm is used to remove the redundant spectral information after band operation, and the edge spectral features are extracted. The U-Net jump connection structure is used to fuse the edge spectral features with the deep convolution network features, and the pixel by pixel classification of softmax is used to extract the cage aquaculture information. Taking the offshore cage aquaculture and deep-sea cage aquaculture in Hainan Island as the research objects, the aquaculture information is extracted. The experimental results show that the accuracy of the proposed method is 97.35% on the offshore cage target and 98.99% on the deep-sea cage target. The result is better than the classical unsupervised algorithms and traditional deep learning model.
- cage aquaculture,
- U-Net model,
- depth feature,
- edge spectral feature

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References(26)

References

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