Improvement of radiographic visibility using an image restoration method based on a simple radiographic scattering model for x-ray nondestructive testing

Kim, K.S.; Kang, Soo‐Hwan; Kim, W.S.; Cho, H.S.; Park, Chulkyu; Lee, D.Y.; Kim, G.A.; Park, Sung Yoon; Lim, Hyunwoo; Lee, H.W.; Park, J.E.; Jeon, Duhee; Lim, Young-Wook; Je, Uikyu; Woo, Tae Ho

doi:10.1016/j.ndteint.2018.05.008

Cited by 22 publications

(11 citation statements)

References 15 publications

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“…In order to better enhance the local area of haze image adaptively, the paper calculates the image depth based on the principle of dark channel [36][37][38]. e principle of dark channel is that the image has three RGB channels, and at least one pixel value is low.…”

Section: Image Depth Clustering Based On Spectral Clustering Algorithmmentioning

confidence: 99%

Image Enhancement Algorithm Based on Depth Difference and Illumination Adjustment

Bao

Yuan

et al. 2021

Scientific Programming

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In order to improve the clarity and color fidelity of traffic images under the complex environment of haze and uneven illumination and promote road traffic safety monitoring, a traffic image enhancement model based on illumination adjustment and depth of field difference is proposed. The algorithm is based on Retinex theory, uses dark channel principle to obtain image depth of the field, and uses spectral clustering algorithm to cluster image depth. After the subimages are divided, the local haze concentration is estimated according to the depth of field and the subimages are adaptively enhanced and fused. In addition, the illumination component is obtained by multiscale guided filtering to maintain the edge characteristics of the image, and the uneven illumination problem is solved by adjusting the curve function. The experimental results show that the proposed model can effectively enhance the uneven illumination and haze weather image in the traffic scene and the visual effect of the images is good. The generated image has rich details, improves the quality of traffic images, and can meet the needs of traffic practical application.

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Section: Image Depth Clustering Based On Spectral Clustering Algorithmmentioning

confidence: 99%

Image Enhancement Algorithm Based on Depth Difference and Illumination Adjustment

Bao

Yuan

et al. 2021

Scientific Programming

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“…Since Wilhelm Röntgen discovered X‐rays in 1985, X‐rays detectors have been widely used in industry, medicine, and research. [ 1–3 ] Since then, in order to make X‐rays detectors with great application potential in crystallography, space exploration, [ 4 ] and nondestructive inspection, [ 5 ] lots of researches have been actively carried out to enhance their performance, [ 6,7 ] and construct effective pixel array. [ 8–10 ] For practical application, in the positron emission tomography (PET), the detection efficiency under 511 keV quantum conditions is the square of the coincidence efficiency.…”

Section: Introductionmentioning

confidence: 99%

Halide Perovskite, a Potential Scintillator for X‐Ray Detection

et al. 2020

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the coincidence efficiency. This indicates that the solid angle controlled by the PET system and the efficiency of the intrinsic detector are greater. [11,12] More significantly, the Compton events in the pulse height spectrum are mainly caused by scattering in the scintillator. Therefore, these deficiencies can be avoided by lowering the threshold. However, the signal provided by Compton scattering quanta in adjacent crystals may be higher than the threshold, and thus may affect the position resolution and make it worse. In X-ray computed tomography (CT), the body is mainly irradiated continuously from multiple directions by fan-shaped X-rays, while attenuation profiles are recorded, and finally reconstructed from the cross-sectional view of the body. [13] This technology mainly uses complex scanning methods in the field of clinical practice. At present, the realized way of X-rays detector can be roughly divided into two types, direct and indirect. The former one directly absorbs incident X-rays, generates electronic signals through semiconductors or engenders chemical signals through thin films. [14-17] This method can directly convert X-rays into visible light without going through other processes. Therefore, an X-ray detector with a wide linear response range, fast pulse rise time, high-energy resolution, and spatial resolution can be obtained, which makes it copiously applied in X-ray detection. [18-21] However, X-ray detectors based on semiconductors face the challenges of high cost and low efficiency. In addition, although the film is cheap, it is difficult to apply in digital form, which may limit its further development. The latter one refers to the conversion of X-rays (in the highenergy radiation, in addition to X-rays, α, β, and γ rays are also included) into ultraviolet visible (UV) light through scintillators which can be further captured by optical devices. [22-24] It consists of a scintillator and an array photodiode (PD). In contrast, since the scintillator that converts X-rays indirectly is cheap, it is easier to implement in the industry than direct detectors, and has the characteristics of low cost and abundant options, stability, and flexible conversion rate. [25,26] At present, indirect X-ray detectors are widely used in ordinary flat panel X-ray detectors. Moreover, it can be flexibly combined with commercially mature sensor arrays (e.g., amorphous silicon PDs, thin film transistor arrays, photomultiplier tubes, complementary metal oxide semiconductors, silicon avalanche PDs, and X-ray imaging charge-coupled devices [CCD]), therefore, they have attracted more attention. Scintillator is a unique class of luminescent materials, which is extensively used in many fields such as nondestructive testing, medical imaging, space probes, etc. Compared with the disadvantages of traditional scintillator materials which have high cost, are fragile, have long response time and low spatial resolution disadvantages, metal halide perovskites are considered to be the most potential scintillator materials in ...

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“…In industrial radiography, non-destructive testing (NDT) is used; it consists of a variety of non-invasive inspection techniques that is used to evaluate material properties, components, or entire process units. Radiographic testing is one of the most frequently used NDT techniques that involve the use of X-rays and digital detector systems, such as amorphous silicon, CCDs and CMOS sensors [12][13][14]. However, beyond the dominance of terbium-doped gadolinium oxysulfide, the interest for CaWO 4 has been renewed in applications such as, particle astrophysics in the quest for dark matter in the universe [15][16][17], for WIMP-nucleon elastic scattering interactions [18,19], as well as, for customs and border control [15,20].…”

Section: Introductionmentioning

confidence: 99%

Imaging performance of a CaWO4/CMOS sensor

Martini

Koukou

Fountos

et al. 2019

Frattura Ed Integrità Strutturale

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The aim of this study was to investigate the modulation transfer function (MTF) and the effective gain transfer function (eGTF) of a nondestructive testing (NDT)/industrial inspection complementary metal oxide semiconductor (CMOS) sensor in conjunction with a thin calcium tungstate (CaWO 4) screen. Thin screen samples, with dimensions of 2.7x3.6 cm 2 and thickness of 118.9 μm, estimated from scanning electron microscopy-SEM images, were extracted from an Agfa Curix universal screen and coupled to the active area of an active pixel (APS) CMOS sensor. MTF was assessed using the slanted-edge method, following the IEC 62220-1-1:2015 method. MTF values were found high across the examined spatial frequency range. eGTF was found maximum when CaWO 4 was combined with charge-coupled devices (CCD) of broadband anti-reflection (AR) coating (17.52 at 0 cycles/mm). The combination of the thin CaWO4 screen with the CMOS sensor provided very promising image resolution and adequate efficiency properties, thus could be also considered for use in CMOS based X-ray imaging devices, for various applications.

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Improvement of radiographic visibility using an image restoration method based on a simple radiographic scattering model for x-ray nondestructive testing

Cited by 22 publications

References 15 publications

Image Enhancement Algorithm Based on Depth Difference and Illumination Adjustment

Image Enhancement Algorithm Based on Depth Difference and Illumination Adjustment

Halide Perovskite, a Potential Scintillator for X‐Ray Detection

Imaging performance of a CaWO4/CMOS sensor

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