The spatial resolution enhancement deconvolution technique of the optimized wiener filter in Terahertz band

Hu, Weidong; Wang, Wenqi; Ji, Jin-jia; Si, Li‐Ming

doi:10.1109/ucmmt.2016.7873975

Cited by 6 publications

(4 citation statements)

References 4 publications

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“…De-convolution is a way of restoring the original image from degraded measurement of the image [1], [22], [23] which is used in many fields for image processing specially in astronomy, passive imaging, microscopic and medical imaging. In order to remove the deformity caused by PSF conventionally Wiener filter based de-convolution methods [13] are used to improve the image quality [24], [25]. The degradation function combined with an additive noise is applied on the input image, , to generate a degraded image g(x,y).…”

Section: Image Reconstructionmentioning

confidence: 99%

De-convolution and De-noising of SAR Based GPS Images Using Hybrid Particle Swarm Optimization

2023

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Synthetic aperture radar (SAR) imaging is an efficient strategy which exploits the properties of microwaves to capture images. A major concern in SAR imaging is the reconstruction of image from back scattered signals in the presence of noise. The reflected signal consist of more noise than the target signal and it is a challenging problem to reduce the noise in the collected signal for better reconstruction of an image. Current studies mostly focus on filtering techniques for noise removal. This can result in an undesirable point spread function causing extreme smearing effect in the desired image. In order to handle this problem, a computational technique, particle swarm optimization (PSO) is used for de-noising purpose and later the target performance is further improved by an amalgamation of Wiener filter. Moreover, to improve the de-noising performance we have exploited the singular value decomposition based morphological filtering. To justify the proposed improvements we have simulated the proposed techniques and results are compared with the conventional existing models. The proposed method revealed considerable decrease in mean square error compared to Wiener filter and PSO techniques. Quantitative analysis of image restoration quality are also presented in comparison with Wiener filter and PSO based on the improvement in signal to noise ratio and peak signal to noise ratio.

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Section: Image Reconstructionmentioning

confidence: 99%

De-convolution and De-noising of SAR Based GPS Images Using Hybrid Particle Swarm Optimization

2023

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“…Nondestructive testing techniques (NDT), which allow inspection without physical or chemical damage to the sample, have become increasingly important in recent years. At present, a variety of nondestructive testing techniques have been proposed to improve the measurement accuracy of thickness, such as ultrasonic [ 4 ] and X-ray [ 5 ] techniques. However, there are some limitations to each testing technology.…”

Section: Introductionmentioning

confidence: 99%

Accurate Characterization of the Adhesive Layer Thickness of Ceramic Bonding Structures Using Terahertz Time-Domain Spectroscopy

Yang

Zhang

et al. 2022

Materials

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Ceramic adhesive structures have been increasingly used in aerospace applications. However, the peaks of the signal on the upper and lower surface of the adhesive layer are difficult to measure directly due to the thin thickness of the adhesive layer and the effect of the attenuation dispersion of the ceramic layer. Thus, the existing non-destructive testing techniques have been ineffective in detecting adhesive quality. In this paper, the thickness of the adhesive layer is measured using terahertz time-domain spectroscopy. A sparse deconvolution method is proposed for the terahertz time-domain spectral signal of ceramic adhesive structures with different adhesive layer thicknesses. The results show that the methods proposed in this paper can realize the separation of reflection signals for glue layers with a thickness of 0.20 mm. By comparing with a wavelet denoising method and a modified covariance method (AR/MCM), the effectiveness of the sparse deconvolution method in estimating the thickness of the glue layer is demonstrated. This work will provide the theoretical and experimental basis for using terahertz time-domain spectroscopy to detect the homogeneity of ceramic adhesive structures.

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“…As a result, some techniques need to be applied to deblur these images. Wiener deconvolution can be useful to deblur the images when the point-spread function (PSF) and noise level are either known or estimated [9,11,12]. The PSF is used to describe the response of an imaging system to a point source or point object.…”

Section: Introductionmentioning

confidence: 99%

Image Enhancement and Corrosion Detection for UAV Visual Inspection of Pressure Vessels

Fei

Yang

et al. 2021

Communications in Computer and Information Science

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The condition of a pressure vessel is normally checked by human operators, which have health and safety risks as well as low working efficiency and high inspection cost. Visual inspection for pressure vessels can be done by an Unmanned Aerial Vehicle (UAV) with the sensing module. Image enhancement techniques and image processing techniques are vital in the UAV inspection of pressure vessels. However, there are several issues to be overcome in the UAV visual inspection of pressure vessels. The images captured by the UAV are of low quality under the cluttered environment due to poor lighting, noises and vibrations caused by the UAV. In this research, a system is developed for UAV visual inspection of pressure vessels using image processing and image enhancement techniques. In the developed system, the input image is captured by the UAV first. Next, efficient image enhancement techniques are applied to the images in order to enhance image qualities. After that, the corrosion part is detected and the percentage of the corrosion area in the entire image is measured.The proposed system has the potential to be implemented for the autonomous correction detection with the image enhancement techniques in UAV visual inspection for the pressure vessels.

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The spatial resolution enhancement deconvolution technique of the optimized wiener filter in Terahertz band

Cited by 6 publications

References 4 publications

De-convolution and De-noising of SAR Based GPS Images Using Hybrid Particle Swarm Optimization

De-convolution and De-noising of SAR Based GPS Images Using Hybrid Particle Swarm Optimization

Accurate Characterization of the Adhesive Layer Thickness of Ceramic Bonding Structures Using Terahertz Time-Domain Spectroscopy

Image Enhancement and Corrosion Detection for UAV Visual Inspection of Pressure Vessels

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