• International Journal of Automotive Technology
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• v.6 no.1
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• pp.53-63
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• 2005

We propose a fuzzy neural network (FNN) theory capable of deciding the quality of a road image prior to extracting lane-related information. The accuracy of lane-related information obtained by image processing depends on the quality of the raw images, which can be classified as good or bad according to how visible the lane marks on the images are. Enhancing the accuracy of the information by an image-processing algorithm is limited due to noise corruption which makes image processing difficult. The FNN, on the other hand, decides whether road images are good or bad with respect to the degree of noise corruption. A cumulative distribution function (CDF), a function of edge histogram, is utilized to extract input parameters from the FNN according to the fact that the shape of the CDF is deeply correlated to the road image quality. A suitability analysis shows that this deep correlation exists between the parameters and the image quality. The input pattern vector of the FNN consists of nine parameters in which eight parameters are from the CDF and one is from the intensity distribution of raw images. Experimental results showed that the proposed FNN system was quite successful. We carried out simulations with real images taken in various lighting and weather conditions, and obtained successful decision-making about $99\%$ of the time.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.188-194
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• 2010

In this paper, the typical Synthetic Aperture Radar (SAR) image quality parameters and analysis method are defined, and the SAR image analysis tool is presented for SAR image evaluation. The structure of the developed SAR image analysis tool consists of four key modules; point target analysis (PTA) module, distributed target analysis (DTA) module, ambiguity analysis (AMA) module, and NESZ analysis (NESZA) module. The developed tool is able to extract the various SAR system parameters from standard SAR product format files. Based on these extracted system parameters, typical SAR image quality parameters are derived from SAR image data.

• Aerospace Engineering and Technology
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• v.1 no.2
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• pp.66-74
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• 2002

The characteristics of the satellite image quality parameters driven by satellite imaging instrument are investigated. Since the satellite image is directly produced by the satellite imaging instrument, the satellite image quality depends on the imager performance highly. This is why the imager performance parameters are considered as an important part of the satellite image quality parameters. The imager performance parameters consist of spectral band parameters, ground sample distance(GSD) parameters, swath width parameters, imager Modulation Transfer Function (MTF), imager Signal to Noise Ratio(SNR), radiometric response characteristics parameters, pixel registration, and imager calibration.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.468-476
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• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• Imaging Science in Dentistry
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• v.47 no.2
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• pp.75-86
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• 2017

Purpose: The purpose of this study was to apply a newly developed free software program, at low cost and with minimal time, to evaluate the quality of dental and maxillofacial cone-beam computed tomography (CBCT) images. Materials and Methods: A polymethyl methacrylate (PMMA) phantom, CQP-IFBA, was scanned in 3 CBCT units with 7 protocols. A macro program was developed, using the free software ImageJ, to automatically evaluate the image quality parameters. The image quality evaluation was based on 8 parameters: uniformity, the signal-to-noise ratio (SNR), noise, the contrast-to-noise ratio (CNR), spatial resolution, the artifact index, geometric accuracy, and low-contrast resolution. Results: The image uniformity and noise depended on the protocol that was applied. Regarding the CNR, high-density structures were more sensitive to the effect of scanning parameters. There were no significant differences between SNR and CNR in centered and peripheral objects. The geometric accuracy assessment showed that all the distance measurements were lower than the real values. Low-contrast resolution was influenced by the scanning parameters, and the 1-mm rod present in the phantom was not depicted in any of the 3 CBCT units. Smaller voxel sizes presented higher spatial resolution. There were no significant differences among the protocols regarding artifact presence. Conclusion: This software package provided a fast, low-cost, and feasible method for the evaluation of image quality parameters in CBCT.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.628-630
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• 2003

Synthetic Aperture Radar(SAR) is an active microwave instrument that performs high-resolution observation under almost all weather condition. Research and algorithms have been proposed to process radar signal and to increase the quality of SAR products. In fact, many complicated steps are involved in order to generate a SAR image product. The purpose of this paper is to derive quality assessment procedures and define important test parameters in each procedure inside a SAR processor. Thus those test parameter values indicate the quality of SAR image products and verify the processor's performance. Moreover, required procedures to correct and handle errors which are indicated during the assessment are also presented.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.329-335
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• 2010

Digital imaging detectors can use a variety of detection materials to convert X-ray radiation either to light or directly to electron charge. Many detectors such as amorphous silicon flat panels, CCDs, and CMOS photodiode arrays incorporate a scintillator screen to convert x-ray to light. The digital radiography systems based on semiconductor detectors, commonly referred to as flat panel detectors, are gaining popularity in the clinical & hospital. The X-ray detectors are described between a-Silicon based indirect type and a-Selenium based direct type. The DRS of detectors is used to convert the x-ray to electron hole pairs. Image processing is described by specific image features: Latitude compression, Contrast enhancement, Edge enhancement, Look up table, Noise suppression. The image features are tuned independently. The final enhancement result is a combination of all image features. The parameters are altered by using specific image features in the different several hospitals. The image in a radiological report consists of two image evaluation processes: Clinical image parameters and MTF is a descriptor of the spatial resolution of a digital imaging system. We used the edge test phantom and exposure procedure described in the IEC 61267 to obtain an edge spread function from which the MTF is calculated. We can compare image in the processing parameters to change between original and processed image data. The angle of the edge with respect to the axes of detector was varied in order to determine the MTF as a function of direction. Each MTF is integrated within the spatial resolution interval of 1.35-11.70 cycles/mm at the 50% MTF point. Each image enhancement parameters consists of edge, frequency, contrast, LUT, noise, sensitometry curve, threshold level, windows. The digital device is also shown to have good uniformity of MTF and image parameters across its modality. The measurements reported here represent a comprehensive evaluation of digital radiography system designed for use in the DRS. The results indicate that the parameter enables very good image quality in the digital radiography. Of course, the quality of image from a parameter is determined by other digital devices in addition to the proper clinical image.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.397-400
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• 2004

Synthetic Aperture Radar(SAR) is an active micro­wave instrument that performs high-resolution observation under almost all weather conditions. Although there are many advantages of SAR instrument, many complicated steps are involved in order to generate SAR image products. Many research and algorithms have been proposed to process radar signal and to increase the quality of SAR products. However, it is hard to find research which compare the quality of SAR products generated with different algorithms and processing methods. In our previous research, a SAR processing s/w was developed for a ground station. In addition, quality assessment procedures and their test parameters inside a SAR processor was proposed. The purpose of this paper is to evaluate the quality of SAR images generated from the developed SAR processing s/w. However, If there are no direct measurements such as radar reflector or scattering field measurement values it is difficult to compare SAR images generated with different methods. An alternative procedures and parameters for SAR image quality evaluation are presented and the problems involved in the comparison methods are discussed. Experiments based on real data have been conducted to evaluate and analyze quality of SAR images.

• Imaging Science in Dentistry
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• v.49 no.2
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• pp.139-151
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• 2019

Purpose: This study was performed to investigate the effect of exposure parameters on image quality obtained using a cone-beam computed tomography (CBCT) scanner and the relationship between physical factors and clinical image quality depending on the diagnostic task. Materials and Methods: CBCT images of a SedentexCT IQ phantom and a real skull phantom were obtained under different combinations of tube voltage and tube current (Alphard 3030 CBCT scanner, 78-90 kVp and 2-8 mA). The images obtained using a SedentexCT IQ phantom were analyzed technically, and the physical factors of image noise, contrast resolution, spatial resolution, and metal artifacts were measured. The images obtained using a real skull phantom were evaluated for each diagnostic task by 6 oral and maxillofacial radiologists, and each setting was classified as acceptable or unacceptable based on those evaluations. A statistical analysis of the relationships of exposure parameters and physical factors with observer scores was conducted. Results: For periapical diagnosis and implant planning, the tube current of the acceptable images was significantly higher than that of the unacceptable images. Image noise, the contrast-to-noise ratio (CNR), the line pair chart on the Z axis, and modulation transfer function (MTF) values showed statistically significant differences between the acceptable and unacceptable image groups. The cut-off values obtained using receiver operating characteristic curves for CNR and MTF 10 were useful for determining acceptability. Conclusion: Tube current had a major influence on clinical image quality. CNR and MTF 10 were useful physical factors that showed significantly associations with clinical image quality.

• Korean Journal of Radiology
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• v.19 no.6
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• pp.1031-1041
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• 2018

Objective: To compare image quality and radiation dose of high-pitch dual-source spiral cardiothoracic computed tomography (CT) between non-electrocardiography (ECG)-synchronized and prospectively ECG-triggered data acquisitions in young children with congenital heart disease. Materials and Methods: Eighty-six children (${\leq}3$ years) with congenital heart disease who underwent high-pitch dual-source spiral cardiothoracic CT were included in this retrospective study. They were divided into two groups (n = 43 for each; group 1 with non-ECG-synchronization and group 2 with prospective ECG triggering). Patient-related parameters, radiation dose, and image quality were compared between the two groups. Results: There were no significant differences in patient-related parameters including age, cross-sectional area, body density, and water-equivalent area between the two groups (p > 0.05). Regarding radiation dose parameters, only volume CT dose index values were significantly different between group 1 ($1.13{\pm}0.09mGy$) and group 2 ($1.07{\pm}0.12mGy$, p < 0.02). Among image quality parameters, significantly higher image noise ($3.8{\pm}0.7$ Hounsfield units [HU] vs. $3.3{\pm}0.6HU$, p < 0.001), significantly lower signal-to-noise ratio ($105.0{\pm}28.9$ vs. $134.1{\pm}44.4$, p = 0.001) and contrast-to-noise ratio ($84.5{\pm}27.2$ vs. $110.1{\pm}43.2$, p = 0.002), and significantly less diaphragm motion artifacts ($3.8{\pm}0.5$ vs. $3.7{\pm}0.4$, p < 0.04) were found in group 1 compared with group 2. Image quality grades of cardiac structures, coronary arteries, ascending aorta, pulmonary trunk, lung markings, and chest wall showed no significant difference between groups (p > 0.05). Conclusion: In high-pitch dual-source spiral pediatric cardiothoracic CT, additional ECG triggering does not substantially reduce motion artifacts in young children with congenital heart disease.