ScanSAR image scallop effect inhibition method based on self-attention mechanism and CycleGAN

A technology of scallop effect and attention, applied in the field of image processing, can solve the problems of unusable, unsuitable image correction processing, low stability of scallop effect removal, etc., to achieve the effect of simplifying the process, improving image quality, and eliminating streaks.

Pending Publication Date: 2021-12-21
SHAANXI NORMAL UNIV
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Problems solved by technology

[0005] The biggest problem with the first type of method is that it needs the prior data information of the radar sensor as support, and cannot only correct the problem image; when there is no way to obtain the original SAR signal or the prior data information of the sensor, this type of method is unavailable
The second type of method is based on image post-processing. A series of processing of images in the spatial domain or frequency domain requires a lot of logical derivation and calculation, so the removal of the scallop effect of images of different platforms and different imaging modes is stable. Sex is not high

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  • ScanSAR image scallop effect inhibition method based on self-attention mechanism and CycleGAN
  • ScanSAR image scallop effect inhibition method based on self-attention mechanism and CycleGAN
  • ScanSAR image scallop effect inhibition method based on self-attention mechanism and CycleGAN

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Embodiment 1

[0038] This embodiment provides a Figure 1 to Figure 12 ScanSAR image scallop effect suppression method based on self-attention mechanism and CycleGAN, including the following steps:

[0039] S1: Crop the ScanSAR image and build a data set;

[0040] S2: Based on the CycleGAN model combined with the self-attention mechanism, a cycle-consistent confrontation generation network model with long-distance dependence is constructed;

[0041] S3: Input the prepared training data set into the neural network model constructed in step 2 for training;

[0042] S4: Input the ScanSAR image with scallop effect into the network model trained in step 3, and the stripe phenomenon of scallop effect can be eliminated.

[0043] Further, the S1: cropping the ScanSAR image, constructing a data set, cutting out 18 scenes of Gaofen No. Several subgraphs with a size of 512*512, which allow some areas to overlap, such as Image 6 , 7 shown. 400 abnormal subimages with scallop effect were screened...

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Abstract

The invention provides a ScanSAR image scallop effect suppression method based on a self-attention mechanism and a CycleGAN. The method comprises the following steps: S1, constructing a ScanSAR image data set; S2, constructing an adversarial generative network model; S3, inputting the data set into the constructed neural network model for training; and S4, inputting the ScanSAR image with the scallop effect into the network model trained in the step 3. According to the ScanSAR image scallop effect suppression method based on the self-attention mechanism and the CycleGAN, the scallop effect of the ScanSAR image is processed. On the basis of the CycleGAN, a novel cyclic consistent adversarial generative network model with long-distance dependence is formed by combining a self-attention mechanism. The method has the capability of more effectively eliminating the scallop effect fringe phenomenon of the image, so that the image quality is obviously improved.

Description

technical field [0001] The invention belongs to the technical field of image processing, and in particular relates to a ScanSAR image scallop effect suppression method based on a self-attention mechanism and CycleGAN. Background technique [0002] Synthetic Aperture Radar (SAR) is an active space microwave remote sensing technology. Scanning Synthetic Aperture Radar (ScanSAR) mode is one of the important working modes of SAR. Scan multiple swaths for greater mapping bandwidth. Due to the scanning mechanism of ScanSAR, its system function is time-varying, and the strength of the received echo signal will change periodically with the position in the azimuth and distance, which makes the ScanSAR image produce serious inhomogeneity. Among them, scalloping is one of the main causes of ScanSAR image inhomogeneity, and it is also an inherent phenomenon in ScanSAR mode. After the imaging process, the energy accumulated in the middle part is higher and the edge is lower, so it pres...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/10G06T5/00
CPCG06T7/10G06T5/005G06T2207/10044G06T2207/30181G06T5/50G06T2207/20084G01S13/9056G01S7/417
Inventor 孙增国彭学俊高嘉谊邓龙彦
Owner SHAANXI NORMAL UNIV
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