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Container cloud-oriented convolutional neural network water body extraction method

A convolutional neural network and water extraction technology, which is applied in the field of interpretation and classification of remote sensing images, and can solve problems such as unproven solutions.

Active Publication Date: 2020-11-24
武汉善睐科技有限公司
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[0005] For the problems in related technologies, no effective solutions have been proposed yet

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  • Container cloud-oriented convolutional neural network water body extraction method
  • Container cloud-oriented convolutional neural network water body extraction method
  • Container cloud-oriented convolutional neural network water body extraction method

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[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments of the present invention belong to the protection scope of the present invention.

[0041] According to an embodiment of the present invention, a container cloud-oriented convolutional neural network water body extraction method is provided.

[0042] Such as figure 1 As shown, the container cloud-oriented convolutional neural network water body extraction method according to the embodiment of the present invention includes the following steps:

[0043] Step S1, obtaining the spectral characteristics of the water body in advance, and selecting bands to form a spectral vector...

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Abstract

The invention discloses a container cloud-oriented convolutional neural network water body extraction method, which relates to the technical field of interpretation and classification of remote sensing images, and comprises the following steps of acquiring spectral characteristics of a water body in advance, and selecting wave bands to form a spectral vector; converting the spectral vector to obtain a spectral feature matrix, and taking the spectral feature matrix as an input feature of a convolutional neural network model; taking the spectral feature matrix as a sample to obtain a water bodyextraction model; carrying out object segmentation on a remote sensing image needing to be subjected to water body extraction through a multi-resolution segmentation algorithm, and identifying each object through a unique ID. The water body is extracted by comprehensively utilizing spectral features and spatial features, so that the influence of shadows on water body extraction can be effectivelyinhibited; and meanwhile, the container cloud and the Spark are used for parallel optimization, so that the efficiency is obviously superior to the efficiency in a single-machine mode, and the efficiency is more obviously improved along with the increase of the data volume.

Description

technical field [0001] The invention relates to the technical field of interpretation and classification of remote sensing images, in particular to a container cloud-oriented convolutional neural network water body extraction method. Background technique [0002] With the rapid development of remote sensing technology, the time resolution and spatial resolution of remote sensing data are getting higher and higher, providing rich data source support for operational monitoring applications in water conservancy, agriculture, environment and other fields. There are many rivers and lakes in my country, how to make full use of remote sensing images to quickly obtain water body information is one of the important tasks of water conservancy monitoring. Especially for areas where floods occur all year round, it is of great significance to accurately and quickly obtain the extent of floods for flood control and disaster reduction. [0003] Due to the low parallelism of traditional re...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/13G06N3/045G06F18/214Y02A10/40
Inventor 张东映梁忠壮黄伟洪志明
Owner 武汉善睐科技有限公司
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