huaqinglong/cv-cfunet

The implementation of CV-CFUNet using tensorflow. (CV-CFUNet: Complex-Valued Channel Fusion UNet for Refocusing of Ship Targets in SAR Images)

CV-CFUNet

The implementation of CV-CFUNet using tensorflow. (CV-CFUNet: Complex-Valued Channel Fusion UNet for Refocusing of Ship Targets in SAR Images)

paper URL：https://ieeexplore.ieee.org/document/10145003

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requirements:

tensorflow ---> 1.10.0

cudatoolkit --> 9.0

cudnn --------> 7.1.4

numpy --------> 1.15.4

scipy --------> 1.5.2

h5py ---------> 2.10.0

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Abstract: In a synthetic aperture radar (SAR) system, target rotation during the coherent integration time results in a time-varying Doppler frequency shift and a blurred image. Blurred images are not conducive to subsequent information interpretation. This paper proposes a complex-valued channel fusion U-shape network (CV-CFUNet) for the three-dimensional rotation refocusing task of ship targets. The proposed method integrates the refocusing task into a blind inverse problem. To take advantage of the amplitude and phase information of complex SAR images, all elements of CV-CFUNet including convolutional layer, activation function, feature maps, and network parameters are extended to the complex domain. The proposed CV-CFUNet is designed by adopting a complex-valued encoder (CV-Encoder), channel fusion module (CFM), and complex-valued decoder (CV-Decoder) to adaptively learn complex features. Experiments on simulated data, GF-3 data, and Sentinel-1 data show that the proposed method achieves significant improvements over existing methods in both efficiency and refocusing accuracy.

cv-cfunet's Issues

Where is the code?

Hi, You said, the code will be published when the paper is published. Where can I find the code