Abstract
In order to shorten the long-term image acquisition time of the terahertz time domain spectroscopy imaging system while ensuring the imaging quality, a hybrid sparsity model (HSM) is proposed for fast terahertz imaging in this paper, which incorporates both intrinsic sparsity prior and nonlocal self-similarity constraints in a unified statistical model. In HSM, a weighted exponentiation shift-invariant wavelet transform is introduced to enhance the sparsity of the terahertz image. Simultaneously, the nonlocal self-similarity by means of the three-dimensional sparsity in the transform domain is exploited to ensure high-quality terahertz image reconstruction. Finally, a new split Bregman-based iteration algorithm is developed to solve the terahertz imaging model more efficiently. Experiments are presented to verify the effectiveness of the proposed approach.
Highlights
The terahertz time domain spectroscopy (THz-TDS) imaging technique is one of the most powerful terahertz imaging techniques, which implements a two-dimensional raster scanning in the object pixel-bypixel to obtain an image with high spatial resolution and high signal-to-noise ratio, so it is very attractive for biomedical imaging [7,8,9]
Inspired by the success of the sparse prior of the image and nonlocal self-similarity in image reconstruction, we propose a novel terahertz imaging strategy by combining both intrinsic sparsity prior and nonlocal self-similarity constraints in a unified statistical model in this paper
The above experimental results show that combining intrinsic sparsity prior and nonlocal self-similarity constraints in a unified statistical model can obtain better reconstruction results of terahertz image
Summary
The terahertz (THz) band is generally considered to cover the frequency range from. 0.1 to 10 THz. In the field of imaging, terahertz radiation has attracted widespread attention with its unique characteristics [1,2,3]. Terahertz could provide higher image resolution due to its shorter wavelength than that of a microwave. The terahertz time domain spectroscopy (THz-TDS) imaging technique is one of the most powerful terahertz imaging techniques, which implements a two-dimensional raster scanning in the object pixel-bypixel to obtain an image with high spatial resolution and high signal-to-noise ratio, so it is very attractive for biomedical imaging [7,8,9]. The spread of the application of THz-TDS technology is hampered by its long image acquisition time
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