Terahertz (THz) imaging has an outstanding advantage of high resolution
due to the high frequency and has promising potential in VideoSAR.
However, limited to the THz source power and the air absorption, the THz
image usually has a low SNR and is susceptible to noise in remote
sensing and imaging. In order to improve the quality of THz images, a
THz image enhancement method is proposed based on the noise2noise idea.
The THz images are reconstructed with the AFBP algorithm. They are
organized as noisy image pairs and filtered with a mask to remove the
influence of moving targets. Then, the Noise2Noise network is
constructed based on the CNN network and takes the noisy image pair as
input and reference. In the training stage, 1000 noisy image pairs are
used as the training set and 100 noisy images are used as the test set
to verify the performance of the proposed method. The experimental
results based on real VideoSAR data demonstrate that the proposed method
is capable of suppressing noise and enhancing the THz image.