Suppression of the fluctuation ef fect in terahertz imaging using homomorphic filtering

Xu, Limin; Wang, Fan; Liu, Jia

doi:10.3788/col201311.081201

Cited by 7 publications

(4 citation statements)

References 9 publications

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“…Histogram equalization, wavelet de‐noising technique, nonlocal mean were applied to enhance image quality and get the clear edge of the THz images 8,9 . Homomorphic filtering method was proposed to suppress the fluctuation effect of THz and enhance target imaging 10 . Mathematical morphology was presented, which can successfully suppress the complex background and increase the peak signal‐to‐noise ratio of THz image 11 .…”

Section: Introductionmentioning

confidence: 99%

“…8,9 Homomorphic filtering method was proposed to suppress the fluctuation effect of THz and enhance target imaging. 10 Mathematical morphology was presented, which can successfully suppress the complex background and increase the peak signal-to-noise ratio of THz image. 11 Other techniques that allows achieving sub-wavelength resolution was THz digital holography.…”

Section: Introductionmentioning

confidence: 99%

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Performance comparison of different deconvolution methods on 2D terahertz imaging

Ning

et al. 2023

Micro & Optical Tech Letters

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Terahertz (THz) images are always to be degraded because of the diffraction phenomenon. In this letter, the wave nature is considered in the resolution enhancement of terahertz imaging. The phase operation is extended to three classical deconvolution algorithms, which are used in THz complex-value deconvolution field. The resolution improvement can be seen, and it is impressive that the resolution can reach 0.5 times of the wavelength via the complex-value total variation deconvolution. We believe that the current resolution of THz imaging system can be significantly upgraded by taking advantage of such approaches.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance comparison of different deconvolution methods on 2D terahertz imaging

Ning

et al. 2023

Micro & Optical Tech Letters

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“…Homomorphic filtering was also adopted to suppress the fluctuation noise, but this method was only suitable for the multiplicative noise using a frequency-domain filter [18]. Morphological reconstruction was applied to suppress the background noise in imaging, but this method is effective only for contours of objects, and it cannot realize image deblurring in the inner parts [18]. Essentially, the measured THz image is a convolution of the object function and the PSF of the imaging system.…”

Section: Introductionmentioning

confidence: 99%

Resolution Enhancement in Terahertz Imaging via Deconvolution

et al. 2019

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Nowadays, terahertz (THz) imaging is quite promising in scientific and biomedical applications. However, the much longer wavelength degrades the resolution of obtained images compared with classical imaging at optical frequencies. Imaging is considered to be a convolution process between the object function and point spread function (PSF) of the system. Thus, how to describe the object accurately from a blurred image is an inverse problem. In this paper, we demonstrate how well such a method can function. We would illustrate how to make current facilities overcome the physical limitations in imaging, which can image at the sub-spot level. Periodical stripes with a period of 0.8 mm are resolved at 0.3 THz. The resolution is 0.32 times the physical size of the focused beam. Moreover, this method is extended to the mathematical operations in a complex domain, which is distinct from previous image studies via visible/IR light. Physically, it means that we essentially deal with phase by making use of the wave nature of THz light. For the first time, it is demonstrated that the reconstructed phase can also describe the shape of the object by applying such an approach. In addition, we have successfully measured the diameter of human hair with a relative error of less than 10% at 3 THz. As an example, we did an experiment on tissues of colorectal cancer and a better image is obtained, which would be helpful for medical diagnosis. We believe that such an approach is able to improve imaging performance at THz frequencies and many applications will gain from it.

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“…It is known that THz imaging has also been confronted with many obstacles. A major problem is the degradation of image quality caused by motion blur [11], low resolution and definition [12,13], and the noises caused by THz source, detector and complex environments [14]. In particular, the intensity interference phenomenon is unavoidable based on continuous-wave (CW) and monochromatic THz imaging systems, including the transmission and reflection geometries, where the repeated fringes will seriously corrupt the image data [15].…”

Section: Introductionmentioning

confidence: 99%

Interference elimination in terahertz imaging based on inverse image processing

Wang¹,

Chen²,

Chen³

et al. 2018

J. Phys. D: Appl. Phys.

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We propose a novel image restoration approach to eliminate the interference fringes in terahertz (THz) imaging. By making use of the information in the background of a THz image, inverse image processing is introduced under a priori knowledge about the degradation mechanism to suppress the interference. Based on a simulated interference image and the original THz image of a piece of paper coated with graphite powder, taken from our continuous THz imaging system, the interference fringes are successfully eliminated. The enhancement of the peak signal-to-noise ratio and structural similarity index is achieved, compared with the frequency domain filtering. Moreover, the inverse image processing is performed on a THz image of fresh rat brain tissue. It presents an excellent result with accurate information for the brain tissue after interference elimination.

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Suppression of the fluctuation ef fect in terahertz imaging using homomorphic filtering

Cited by 7 publications

References 9 publications

Performance comparison of different deconvolution methods on 2D terahertz imaging

Performance comparison of different deconvolution methods on 2D terahertz imaging

Resolution Enhancement in Terahertz Imaging via Deconvolution

Interference elimination in terahertz imaging based on inverse image processing

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