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Compressed sensing and cleaning algorithm combined image reconstruction method and system

A technology of compressed sensing and image reconstruction, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as image aliasing and inability to obtain reconstructed images

Inactive Publication Date: 2021-02-05
NAT SPACE SCI CENT CAS
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Problems solved by technology

[0004] The purpose of the present invention is to solve the problem that in the case of sparse sampling in passive microwave interference imaging, due to serious image aliasing, the traditional CLEAN algorithm cannot obtain a higher-quality reconstructed image. In order to improve the quality of the reconstructed image, the present invention provides a compression Image reconstruction method and system combining perception and cleaning algorithm

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  • Compressed sensing and cleaning algorithm combined image reconstruction method and system
  • Compressed sensing and cleaning algorithm combined image reconstruction method and system
  • Compressed sensing and cleaning algorithm combined image reconstruction method and system

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Embodiment 1

[0095] Such as figure 1 As shown, Embodiment 1 of the present invention proposes an image reconstruction method combining compressed sensing and cleaning algorithms. Specific steps are as follows:

[0096] Step 1) Find a suitable sparse domain and establish an objective function according to the principle of compressed sensing, and obtain the CS reconstruction image through an iterative algorithm;

[0097] Step 2) Perform Fourier transform on the CS reconstructed image, and obtain the frequency domain visibility function value of the sampling baseline position; make a difference between the original image sampling value and the frequency domain value and perform inverse Fourier transform to obtain the remaining inversion image ;

[0098] Step 3) Using the CLEAN method to perform a cleaning operation on the remaining inversion image to obtain the remaining reconstructed image;

[0099] Step 4) Add the CS reconstruction image calculated and obtained in step 2) to the remainin...

Embodiment 2

[0145] Such as Figure 12 As shown, Embodiment 2 of the present invention proposes an image reconstruction system combining compressed sensing and cleaning algorithm, the system includes: compressed sensing reconstruction image generation module 100, residual inversion image generation module 200, cleaning processing module 300 and reconstructed image generation module 400; wherein,

[0146] The compressed sensing reconstructed image generating module 100 is used to find a suitable sparse domain for the sparse brightness temperature distribution image according to the compressed sensing principle and establish an objective function, and obtain the compressed sensing reconstructed image through an iterative algorithm;

[0147] The remaining inversion image generation module 200 is used to perform Fourier transform on the compressed sensing reconstruction image, and obtain the frequency domain visibility function value of the sampling baseline position; make a difference between...

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Abstract

The invention discloses a compressed sensing and cleaning algorithm combined image reconstruction method and system, and the method comprises the steps: 1), searching an appropriate sparse domain fora sparse brightness temperature distribution image according to a compressed sensing principle, building an objective function, and solving a compressed sensing reconstruction image through an iterative algorithm; 2) performing Fourier transform on the compressed sensing reconstructed image, obtaining a frequency domain visibility function value of a sampling baseline position, subtracting the original image sampling value from the frequency domain value, and performing inverse Fourier transform to obtain a residual inversion image; 3) performing cleaning operation on the residual inversion image by adopting a cleaning method to obtain a residual reconstructed image; and 4) adding the compressed sensing reconstructed image and the remaining reconstructed image to obtain a final reconstructed image. The method provided by the invention aims at the problem of serious image aliasing under the condition of sparse sampling in passive microwave interference imaging, and improves the qualityof a reconstructed image.

Description

technical field [0001] The invention relates to the field of passive microwave interference imaging, to the field of passive microwave interference image reconstruction under sparse sampling conditions, and in particular to an image reconstruction method and system combining compressed sensing and cleaning algorithms. Background technique [0002] Passive microwave interferometry essentially measures the Fourier component of the spatial distribution of signals by cross-correlating signals received at different points in space. If we make an analogy with the usual time series signal processing, the space here is equivalent to time, the distribution of the signal in space is equivalent to the usual time domain signal, and the interferometry gives its frequency domain signal, using the comprehensive imaging method, through the The Fourier transform of the visibility function obtained by the interference processing is used to invert the spatial distribution of the signal, and th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50G06T7/73
CPCG06T5/50G06T2207/20056G06T2207/20221G06T2207/20224G06T7/73
Inventor 段然邓丽杨震
Owner NAT SPACE SCI CENT CAS
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