High resolution image semantic information extraction method and system

An information extraction and high-resolution technology, applied in the field of high-resolution image semantic information extraction methods and systems, can solve problems such as the inability to guarantee existing prior knowledge

Active Publication Date: 2017-08-25
WUHAN UNIV
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Problems solved by technology

However, in the process of increasing the number of network layers, it is accompanied by the consumption of expensive graphics card storage unit (GPU), and the prior knowledg

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  • High resolution image semantic information extraction method and system
  • High resolution image semantic information extraction method and system

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Embodiment Construction

[0062] In order to better understand the technical solution of the present invention, the present invention will be further described below in conjunction with the accompanying drawings. The DMSMR neural network framework that the present invention proposes sees figure 2 , each convolutional layer or dilated convolutional layer implicitly contains a modified linear unit "ReLU" layer as the activation function. network network.

[0063] The technical means involved in the present invention will be described in detail below.

[0064] (1) Multi-label manifold sorting method based on graph model.

[0065] The multi-label manifold sorting method is an extension of the two-category manifold sorting method. The following first introduces the two-category manifold sorting method, and then extends to the multi-label manifold sorting method.

[0066] The details of the two-category manifold sorting method include:

[0067] 1.1.1 Determine the weight matrix W.

[0068] Suppose ther...

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Abstract

The invention discloses a high resolution image semantic information extraction method and system. According to the method, a dual multi-scale manifold sorting convolutional neural network is employed to solve a high resolution image semantic information extraction problem, multi-scale information characteristics of a pooling layer of the convolutional neural network are utilized, a multi-scale convolutional-expansion convolutional dual network layer is constructed, a continuous domain inner manifold sorting optimization method is further employed, and multi-scale space results are optimized. The method is advantaged in that the multi-scale optimization results are utilized, fusion processing on the extracted semantic information is carried out in a mean value fusion mode, and thereby the final semantic segmentation result of high resolution images is acquired.

Description

technical field [0001] The invention relates to the fields of pattern recognition and remote sensing, in particular to a method and system for extracting semantic information from high-resolution images. Background technique [0002] The semantic information technology of high-resolution images, including ground close-range images and high-resolution aerial satellite images, is one of the important research topics in the field of pattern recognition and remote sensing. In recent years, with the development of ground close-range image acquisition technology and aerospace platforms, massive high-resolution image data has been widely used in unmanned driving, map surveying, geographic census, and artificial ground object detection. However, due to differences in image acquisition platforms and image scales, see figure 1 However, the image interpretation process still largely relies on manual visual interpretation and delineation, and its low efficiency is rooted in the fact th...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/13G06F18/2415G06F18/214
Inventor 胡翔云张觅赵丽科
Owner WUHAN UNIV
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