Numerical image enhancement for THz time-domain spectroscopy

Schildknecht, Christian; Kleine‐Ostmann, Thomas; Knobloch, P.; Rehberg, E.; Koch, Martin

doi:10.1109/thz.2002.1037617

Cited by 7 publications

(9 citation statements)

References 20 publications

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“…Step 2: Optimized transmission ( ) dark is the minimum value of three channels in each pixel. According to (9), the color of the air in a hazy image is usually very similar to the atmospheric light A. µ is set to 0.3.…”

Section: A: Reconstructed Modelmentioning

confidence: 99%

Terahertz Image Enhancing Based on the Physical Model and Multiscale Retinex Algorithm

Mao¹,

Zhu²,

liu³

et al. 2021

Preprint

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To settle the THz image degradation problem, we propose an effective enhancement method based on the physical model and multiscale retinex (MSR) algorithm. The overall enhancing process involves two parts: reconstruction and enhancement. Firstly, the original THz images are reconstructed by a mathematical model, which is built and considered the THz absorption variate and Gaussian distribution of the beam. Then, the original images are processed by the proposed algorithm, which is combined the atmospheric scattering model and optimized MSR algorithm. The proposed algorithm not only recover the image scene radiance and remove haze, but also can make a compromise of the dynamic range of grayscale and edge enhancement of image. Results on a variety of THz images demonstrate our method can effectively improve the quality of THz images and retain sufficient image details.

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Section: A: Reconstructed Modelmentioning

confidence: 99%

Terahertz Image Enhancing Based on the Physical Model and Multiscale Retinex Algorithm

Mao¹,

Zhu²,

liu³

et al. 2021

Preprint

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show abstract

“…(8) Where δ(y s , y t )=-1 if y s =y t ; δ(y s , y t )=1 if y s ≠y t . And γ is a constant which can be specified as a priori information.…”

Section: Denoising Based On Markov Random Fieldmentioning

confidence: 99%

“…In THz CW scanning imaging system, the fluctuation of laser output power and the aperture effects of a finite focus diameter have a big influence on imaging quality, which reduces the image resolution and causes the imaging noise [6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

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Continuous-wave THz image denoising based on Markov random field and simulated annealing algorithm

Yin

Yao

et al. 2009

SPIE Proceedings

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In Terahertz continuous-wave laser scanning imaging system, the laser output power's fluctuation and the aperture effects of a finite focus diameter have significant influence on the image quality, which reduces the image resolution and causes the imaging noise. The most common problem of image denoising is that some interesting structures in the image will be removed from the concerned image during noise suppression. Because Markov random field (MRF) can be used to describe the spatial continuity, the structures of images can be modeled if a proper neighborhood system is selected.Therefore, MRF and simulated annealing are used to suppress the image noise and increase the image resolution.Simulation and experiment show that the method can preserve the object structures of THz images.

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“…Trofimov et al used a convolution function instead of a correlation function between the Fourier transform and a standard image; additionally, an edge sharpening algorithm was used to enhance terahertz image quality [8]- [10]. Schildknecht et al proposed a blind deconvolution method for terahertz images and estimated the corresponding PSF values; by using a beam of 0.5-0.75 THz, they observed traces of 1 mm narrow slits in metal test structures [11]. Zhang et al found that a THz image in the frequency domain contains more information than a THz image in the time domain; they also proposed an imaging algorithm based on deconvolution, which can improve the depth resolution of multilayer object detection and imaging [12].…”

Section: Introductionmentioning

confidence: 99%

Time Segmented Image Fusion Based Multi- Depth Defects Imaging Method in Composites With Pulsed Terahertz

et al. 2020

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Recently, terahertz (THz) nondestructive testing technology has prevailed in the defect detection of composite materials yet is limited by identifying deeper flaws. To solve this problem, a timedomain piecewise imaging method based on terahertz signal extraction is proposed in this article. First, the surface reflection echo signal is removed by applying a time correction, and the time-domain signal is then segmented according to the thickness of the sample. Finally, high-quality terahertz images are obtained by image fusion technology. All imaging methods, including traditional ones, are utilized to detect defects in glass fiber reinforced plastic (GFRP) sample then the signal-to-noise ratio (SNR) and defect edge contrast of each method are calculated. The experimental results show that the proposed method can effectively improve the terahertz imaging of deeper defects in GFRP sample especially for multi-depth defects and possesses the highest SNR and defect edge contrast.

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Numerical image enhancement for THz time-domain spectroscopy

Cited by 7 publications

References 20 publications

Terahertz Image Enhancing Based on the Physical Model and Multiscale Retinex Algorithm

Terahertz Image Enhancing Based on the Physical Model and Multiscale Retinex Algorithm

Continuous-wave THz image denoising based on Markov random field and simulated annealing algorithm

Time Segmented Image Fusion Based Multi- Depth Defects Imaging Method in Composites With Pulsed Terahertz

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