Phase unwrapping method and device based on composite neural network

A neural network and neural network model technology, applied in neural learning methods, biological neural network models, neural architectures, etc.

Pending Publication Date: 2020-10-20
SOUTH CHINA NORMAL UNIVERSITY
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

These algorithms can restore the wrapped phase map, but they still cannot effec

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  • Phase unwrapping method and device based on composite neural network
  • Phase unwrapping method and device based on composite neural network
  • Phase unwrapping method and device based on composite neural network

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Embodiment Construction

[0042] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention.

[0043] In some processes described in the specification and claims of the present invention and the above-mentioned drawings, a plurality of operations appearing in a specific order are contained, but it should be clearly understood that these operations may not be performed in the order in which they appear herein Execution or parallel execution, the serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. Additionally, these processes can include more or fewer operations, and these operations can be performed sequentially or in parallel. It should ...

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Abstract

The invention discloses a phase unwrapping method and device based on a composite neural network, and the method comprises: generating a data set through employing simulation software; randomly dividing the data set into a training set and a test set; preprocessing the wrapped phase data in the training set to obtain a processed training set; fusing the U-shaped network U-Net, the image segmentation network SegNet and the residual network to construct a composite neural network model comprising a convolutional layer and a pooling layer; performing model training through a composite neural network model and the processed training set to determine and store network model parameters of the composite neural network model; and taking the wrapped phase data in the test set as the input of the composite neural network model so as to carry out phase unwrapping on the wrapped phase data in the test set to obtain corresponding actual unwrapped phase data, and determining the accuracy of the composite neural network model according to the actual unwrapped phase data and the target unwrapped phase data.

Description

technical field [0001] The present invention relates to the technical field of image processing, more specifically, to a phase unwrapping method and device based on a composite neural network. Background technique [0002] Phase unwrapping is to recover the real phase information from the wrapped (entangled) phase, and it has a wide range of applications in optical interferometry (holographic interferometry, speckle interferometry), synthetic aperture radar interferometry, medical imaging and other fields. Because the phase obtained by these techniques generally uses the arctangent function, the phase is wrapped in the range of (-π, π), thus showing a discontinuous distribution. This is not the real phase value. In order to get the actual phase, it is necessary to perform phase unwrapping on the wrapped phase. [0003] The current phase unwrapping algorithms are mainly divided into two categories. One is the global expansion algorithm, which transforms the phase unwrapping...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/084G06N3/044G06F2218/22G06F2218/08
Inventor 刘胜德黄韬吕晓旭
Owner SOUTH CHINA NORMAL UNIVERSITY
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