THz imaging enhancement based on Noise2Noise algorithm. Issue 5 (2nd March 2023)

• Record Type: Journal Article
• Authors: Wang, Tianhe; Huang, Xuejun; Ding, Jinshan; Zhang, Yuhong
• Is Part Of: Electronics letters. Volume 59:Issue 5(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2023-03-02
• Subjects: image enhancement -- terahertz wave imaging; Electronics -- Periodicals; 621.381
• DOI: 10.1049/ell2.12743
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract: 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 strategy. The THz images are reconstructed using 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 of real VideoSAR data have demonstrated that the proposed method is capable of suppressing noise and enhancing the THz image. Abstract : A THz image enhancement method is proposed based on the noise2noise idea to improve the quality of THz images. The THz images are organized as noisy image pairs and filtered with a mask to remove the influence of moving targets and mismatches on the edges. The network is constructed based on the CNN networks and 1000 noisy image pairs are used as the training set. 100 noisy images of real THz images are used to test 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.