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An ice cover radar image ice layer fine segmentation method based on an FCN-ASPP network

A radar image and refinement technology, which is applied in the fields of computer vision and pattern recognition, can solve the problems of insufficient segmentation and refinement, and achieve the effects of improving classification and judgment efficiency, reducing consumption, and achieving refinement and robustness

Active Publication Date: 2019-05-10
BEIJING UNIV OF TECH
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Problems solved by technology

However, the FCN segmentation network also has the disadvantage of insufficient segmentation refinement. Based on the FCN segmentation network, the method in this paper improves it, strengthens the fine segmentation ability of the network, and makes it more in line with the requirements of ice radar image segmentation.

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  • An ice cover radar image ice layer fine segmentation method based on an FCN-ASPP network
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Embodiment Construction

[0033] Describe in detail below in conjunction with accompanying drawing:

[0034] The technical block diagram of the present invention is as figure 1 shown. The specific implementation steps are as follows:

[0035] 1. Pretreatment

[0036] The first step is to logarithmically transform the collected radar amplitude image, and calculate the radar amplitude a by formula (1) i The corresponding pixel value b i

[0037] b i =20×log10(a i ) (1)

[0038] In the second step, the image is normalized by formula (2), and the image is normalized to 255 pixel levels.

[0039]

[0040] Among them, bi is the logarithmically transformed pixel value, c i is the pixel value after normalization, max is the maximum value of the pixel before normalization, and min is the minimum value of the pixel before normalization.

[0041] The third step is to perform Lee filter processing on the original image to eliminate the coherent speckle noise of the radar image, and save the obtained ...

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Abstract

The invention discloses an ice cover radar image ice layer fine segmentation method based on an FCN-ASPP network, and relates to the field of computer vision and mode recognition. According to the invention, the radar amplitude image is used as a training sample of a network, corresponding data amplification is carried out for the problem of less ice layer image data, and the wide applicability ofthe method is expanded. Lee filtering is carried out on the ice cover image. In order to save edge information as much as possible, a threshold judgment process is added to a filtering process. FCN-is constructed, and FCN-is constructed; according to the ASPP ice layer segmentation deep network, the ASPP layer is improved, so that the extraction capability of the network on small-scale characteristics is enhanced. The preliminary classification result is further processed through CRF, and the segmentation result is further refined on the basis of achieving end-to-end pixel level segmentation.In addition, the network greatly realizes the autonomous learning process.

Description

technical field [0001] The invention belongs to the field of computer vision and pattern recognition, and relates to a method for ice layer segmentation of ice sheet radar images based on deep learning. Background technique [0002] In recent years, global warming has seriously threatened our living environment. The Antarctic ice sheet has melted at an accelerated rate in recent decades, causing sea level rise and having a considerable impact on ocean currents. It may even lead to serious geological disasters. Therefore, collecting data on the thickness, distribution, etc. of the polar ice caps and how they change over time can be useful in understanding and predicting the impact of melting glaciers. Radar sensors are one of the instruments that can penetrate the ice and provide topographical information on large areas under the ice. Because air, ice, and rock have different dielectric constants, radar waves backscatter differently when passing through different media obj...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/11G06K9/00
Inventor 蔡轶珩马杰胡绍斌李媛媛
Owner BEIJING UNIV OF TECH
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