• IEIE Transactions on Smart Processing and Computing
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• v.3 no.2
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• pp.41-51
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• 2014

This paper describes a method to estimate the noise power using the minimum statistics approach, which was originally proposed for audio processing. The proposed minimum statistics-based method separates a noisy image into multiple frequency bands using the three-level discrete wavelet transform. By assuming that the output of the high-pass filter contains both signal detail and noise, the proposed algorithm extracts the region of pure noise from the high frequency band using an appropriate threshold. The region of pure noise, which is free from the signal detail part and the DC component, is well suited for minimum statistics condition, where the noise power can be extracted easily. The proposed algorithm reduces the computational load significantly through the use of a simple processing architecture without iteration with an estimation accuracy greater than 90% for strong noise at 0 to 40dB SNR of the input image. Furthermore, the well restored image can be obtained using the estimated noise power information in parametric image restoration algorithms, such as the classical parametric Wiener or ForWaRD image restoration filters. The experimental results show that the proposed algorithm can estimate the noise power accurately, and is particularly suitable for fast, low-cost image restoration or enhancement applications.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.542-543
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• 2012

Coherent diffraction imaging (CDI) method using hard x-ray at 5.46 keV was applied to study assembly of Ni and Ni oxide nano structures formed on a Si3N4 membrane. Density distribution of Ni nano-particles was obtained quantitatively with about 15 nm lateral resolution by reconstructing images from the speckle diffraction pattern. In addition, reconstructed images of nickel oxide particles indicated that Ni atoms diffuse out during the oxidation process leaving pores inside the nickel oxide crust. Furthermore, we recognize that really weak phase object, less than 5 nm thickness of Ni residues, can be reconstructed due to the reference particles. We achieved quantitative information of nanometer sized materials and demonstrate the effect of reference particles by using hard x-ray coherent diffractive imaging method.

• Journal of Biosystems Engineering
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• v.38 no.3
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• pp.199-207
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• 2013

Purpose: Tomatoes, an important agricultural product in fresh-cut markets, are sometimes a source of foodborne illness, mainly Salmonella spp. Growth cracks on tomatoes can be a pathway for bacteria, so its detection prior to consumption is important for public health. In this study, multispectral Visible/Near-Infrared (NIR) reflectance imaging techniques were used to determine optimal wavebands for the classification of defect tomatoes. Methods: Hyperspectral reflectance images were collected from samples of naturally cracked tomatoes. To classify the resulting images, the selected wavelength bands were subjected to two-band permutations, and a supervised classification method was used. Results: The results showed that two optimal wavelengths, 713.8 nm and 718.6 nm, could be used to identify cracked spots on tomato surfaces with a correct classification rate of 91.1%. The result indicates that multispectral reflectance imaging with optimized wavebands from hyperspectral images is an effective technique for the classification of defective tomatoes. Conclusions: Although it can be susceptible to specular interference, the multispectral reflectance imaging is an appropriate method for commercial applications because it is faster and much less expensive than Near-Infrared or fluorescence imaging techniques.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.5
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• pp.687-698
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• 2012

LADAR systems can rapidly acquire 3D point clouds by sampling the target surfaces using laser pulses. Such point clouds are widely used for diverse applications such as DSM/DTM generation, forest biomass estimation, target detection, wire avoidance and so on. Many kinds of LADAR systems have been developed with their respective purposes and applications. Particularly, Geiger mode imaging LADAR systems are increasingly utilized since they are energy efficient thank to extremely sensitive detectors incorporated into the systems. The purpose of this research is the performance assessment of a Geiger mode imaging LADAR system based on simulation with the real system parameters. We thus developed a simulation method of such a LADAR system by modeling its geometric, radiometric, optic and electronic aspects. Based on the simulation, we performed the performance assessment of a newly designed system to derive the outlier ratio and false alarm rate expected during its operation in almost real environment with reasonable system parameters. The proposed simulation and performance assessment method will be effectively utilized for system design and optimization, and test data generation.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.51-59
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• 2016

In this paper we present (1) analysis of imaging sonar measurement for two-view relative pose estimation of an autonomous vehicle and (2) bundle adjustment and 3D reconstruction method using imaging sonar. Sonar has been a popular sensor for underwater application due to its robustness to water turbidity and visibility in water medium. While vision based motion estimation has been applied to many ground vehicles for motion estimation and 3D reconstruction, imaging sonar addresses challenges in relative sensor frame motion. We focus on the fact that the sonar measurement inherently poses ambiguity in its measurement. This paper illustrates the source of the ambiguity in sonar measurements and summarizes assumptions for sonar based robot navigation. For validation, we synthetically generated underwater seafloor with varying complexity to analyze the error in the motion estimation.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2341-2347
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• 2021

Because single-photon emission computed tomography (SPECT) is one of the widely used nuclear medicine imaging systems, it is extremely important to acquire high-quality images for diagnosis. In this study, we designed a super-resolution (SR) technique using dense block-based deep convolutional neural network (CNN) and evaluated the algorithm on real SPECT phantom images. To acquire the phantom images, a real SPECT system using a^99mTc source and two physical phantoms was used. To confirm the image quality, the noise properties and visual quality metric evaluation parameters were calculated. The results demonstrate that our proposed method delivers a more valid SR improvement by using dense block-based deep CNNs as compared to conventional reconstruction techniques. In particular, when the proposed method was used, the quantitative performance was improved from 1.2 to 5.0 times compared to the result of using the conventional iterative reconstruction. Here, we confirmed the effects on the image quality of the resulting SR image, and our proposed technique was shown to be effective for nuclear medicine imaging.

• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.82-86
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• 2017

High dynamic range (HDR) imaging offers a radically approach of representing colors in digital images. Instead of using the range of colors produced by given devices, HDR imaging method manipulates and stores all colors and brightness levels visible to the human eye. To faithfully represent, store and then reproduce all these effects, the original scene must be stored and treated using high fidelity HDR techniques. Then, tone mapping is required to accommodate HDR image to low dynamic range (LDR) devices, and tone mapping operation of HDR image for realistic display is commonly researched. However, color visualization for analyzing scene luminance in HDR imaging has less attention from researches. This paper presents and implements a method for reproduction and visualization of the false color in HDR images. We produce a color visualization framework with several mapping functions, and evaluate their effectiveness by using RMAE and SNR with commonly used HDR image data. Experiment reveals that the sigmodal mapping function shows better performance in the false color visualization, compared to other methods.

• Investigative Magnetic Resonance Imaging
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• v.23 no.1
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• pp.26-33
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• 2019

Purpose: Diffusion tensor imaging (DTI) data must be analyzed by an analyzer after data processing. Hence, the analyzed data of DTI might depend on the analyzer, making it a major limitation. This paper reviewed previous DTI studies reporting the repeatability and reproducibility of data from the corticospinal tract (CST), one of the most actively researched neural tracts on this topic. Materials and Methods: Relevant studies published between January 1990 and December 2018 were identified by searching PubMed, Google Scholar, and MEDLINE electronic databases using the following keywords: DTI, diffusion tensor tractography, reliability, repeatability, reproducibility, and CST. As a result, 15 studies were selected. Results: Measurements of the CSTs using region of interest methods on 2-dimensional DTI images generally showed excellent repeatability and reproducibility of more than 0.8 but high variability (0.29 to 1.00) between studies. In contrast, measurements of the CST using the 3-dimensional DTT method not only revealed excellent repeatability and reproducibility of more than 0.9 but also low variability (repeatability, 0.88 to 1.00; reproducibility, 0.82 to 0.99) between studies. Conclusion: Both 2-dimensional DTI and 3-dimensional DTT methods appeared to be reliable for measuring the CST but the 3-dimensional DTT method appeared to be more reliable.

• Imaging Science in Dentistry
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• v.51 no.2
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• pp.107-115
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• 2021

Purpose: This study aimed to demonstrate the presence of dental caries through a photoacoustic imaging system with visible and near-infrared wavelengths, highlighting the differences between the 2 spectral regions. The depth at which carious tissue could be detected was also verified. Materials and Methods: Fifteen permanent molars were selected and classified as being sound or having incipient or advanced caries by visual inspection, radiography, and optical coherence tomography analysis prior to photoacoustic scanning. A photoacoustic imaging system operating with a nanosecond pulsed laser as the light excitation source at either 532 nm or 1064 nm and an acoustic transducer at 5 MHz was developed, characterized, and used. En-face and lateral(depth) photoacoustic signals were detected. Results: The results confirmed the potential of the photoacoustic method to detect caries. At both wavelengths, photoacoustic imaging effectively detected incipient and advanced caries. The reconstructed photoacoustic images confirmed that a higher intensity of the photoacoustic signal could be observed in regions with lesions, while sound surfaces showed much less photoacoustic signal. Photoacoustic signals at depths up to 4 mm at both 532 nm and 1064 nm were measured. Conclusion: The results presented here are promising and corroborate that photoacoustic imaging can be applied as a diagnostic tool in caries research. New studies should focus on developing a clinical model of photoacoustic imaging applications in dentistry, including soft tissues. The use of inexpensive light-emitting diodes together with a miniaturized detector will make photoacoustic imaging systems more flexible, user-friendly, and technologically viable.

• Investigative Magnetic Resonance Imaging
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• v.26 no.2
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• pp.117-124
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• 2022

Purpose: In this study, we provide a way to assess even a slight effect of exercise on trunk-muscle activity. Materials and Methods: Seven healthy male participants (mean age, 24.7 ± 3.2 years; height, 171.2 ± 9.8 cm; and weight, 63.8 ± 11.9 kg) performed 15 sets of an exercise with 20 repetitions of 90° hip and right-knee flexion while lying supine. The exercise intensity was measured using the 10-point Rating of Perceived Exertion Scale after the first and 15th sets of exercises. Although cross-sectional areas and functional T2 mapping using ultrafast imaging (fast-acquired muscle functional magnetic resonance imaging, fast-mfMRI) have been proposed for imaging to evaluate exercise-induced muscle activity in real time, no previous studies have reported on the evaluation of trunk-muscle activity using functional T2 mapping. As a method for assessing trunk-muscle activity, we compared functional T2 mapping using ultrafast imaging (fast-mfMRI) with cross-sectional areas. Results: Although the muscle cross-sectional areas were increased by the exercise, there was no significant difference at rest. On the other hand, for all sets, the changes in T2 were significant compared with those at rest (P < 0.01). These results demonstrate that T2, calculated from fast-mfMRI images can be used to detect even a small amount of muscle activity induced by acute exercise, which was impossible to do with cross-sectional areas. Conclusion: Fast-mfMRI, which can also display functional information with detailed forms, enabled non-invasive real-time imaging for identifying and evaluating the degree of deep trunk-muscle activity induced by exercise.