• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.51-60
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• 2024

Aiming at the problem of low contrast and difficult to recognize video images in low-light environment, we propose an adaptive contrast compensation enhancement algorithm based on human visual perception. First of all, the video image characteristic factors in low-light environment are extracted: AL (average luminance), ABWF (average bandwidth factor), and the mathematical model of human visual CRC(contrast resolution compensation) is established according to the difference of the original image's grayscale/chromaticity level, and the proportion of the three primary colors of the true color is compensated by the integral, respectively. Then, when the degree of compensation is lower than the bright vision precisely distinguishable difference, the compensation threshold is set to linearly compensate the bright vision to the full bandwidth. Finally, the automatic optimization model of the compensation ratio coefficient is established by combining the subjective image quality evaluation and the image characteristic factor. The experimental test results show that the video image adaptive enhancement algorithm has good enhancement effect, good real-time performance, can effectively mine the dark vision information, and can be widely used in different scenes.

• Korean Journal of Materials Research
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• v.22 no.11
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• pp.636-641
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• 2012

In this study, we have investigated highly efficient nanoscale surface corrugated light emitting diodes (LEDs) for the enhancement of light extraction efficiency (LEE) of nitride semiconductor LEDs. Nanoscale indium tin oxide (ITO) surface corrugations are fabricated by using the conformal nanoimprint technique; it was possible to observe an enhancement of LEE for the ITO surface corrugated LEDs. By incorporating this novel method, we determined that the total output power of the surface corrugated LEDs were enhanced by 45.6% for patterned sapphire substrate LEDs and by 41.9% for flat c-plane substrate LEDs. The enhancement of LEE through nanoscale surface corrugations was studied using 3-dimensional Finite Different Time Domain (FDTD) calculation. From the FDTD calculations, we were able to separate the light extraction from the top and bottom sides of device. This process revealed that light extraction from the top and bottom sides of a device strongly depends on the substrate and the surface corrugation. We found that enhanced LEE could be understood through the mechanism of enhanced light transmission due to refractive index matching and the increase of light scattering from the corrugated surface. LEE calculations for the encapsulated LEDs devices also revealed that low LEE enhancement is expected after encapsulation due to the reduction of the refractive index contrast.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.442-453
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• 2020

Underwater color images suffer from low visibility and color cast effects caused by light attenuation by water and floating particles. This study applied single image enhancement techniques to enhance the quality of underwater images and compared their performance with real underwater images taken in Korean waters. Dark channel prior (DCP), gradient transform, image fusion, and generative adversarial networks (GAN), such as cycleGAN and underwater GAN (UGAN), were considered for single image enhancement. Their performance was evaluated in terms of underwater image quality measure, underwater color image quality evaluation, gray-world assumption, and blur metric. The DCP saturated the underwater images to a specific greenish or bluish color tone and reduced the brightness of the background signal. The gradient transform method with two transmission maps were sensitive to the light source and highlighted the region exposed to light. Although image fusion enabled reasonable color correction, the object details were lost due to the last fusion step. CycleGAN corrected overall color tone relatively well but generated artifacts in the background. UGAN showed good visual quality and obtained the highest scores against all figures of merit (FOMs) by compensating for the colors and visibility compared to the other single enhancement methods.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.87-96
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• 2019

Improvement of low-light image mainly focuses on the contrast enhancement. Many researches have been carried out for brightness enhancement, contrast improvement and illumination reduction. Recently, the aforementioned approaches have been replaced by artificial neural networks. This paper proposes a methodology that can replace the Retinex-based reflectance image acquisition by deep neural network. Experiments carried out on 102 low-light images validated the feasibility of the replacement by producing PSNR=30.8682(db) and SSIM=0.4345.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.36-41
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• 2018

An image intensifying device is equipment that makes weak objects visible in a dark environment, such as making nighttime bright enough to let objects be visually observed. It is possible to obtain a clear image by amplifying the light in the presence of a certain amount of weak light. However, in an extremely low-light environment, where even moonlight is not present, there is not enough light to amplify anything, and the sharpness of the screen deteriorates. In this paper, a method is proposed to improve image quality by using multiple filters and anisotropic diffusion for output noise of the image-intensifying device in extreme low-light environments. For the experiment, the output of the image-intensifying device was obtained under extremely low-light conditions, and signal processing for improving the image quality was performed. The configuration of the filters for signal processing uses anisotropic diffusion after applying a median filter and a Wiener filter for effective removal of salt-and-pepper noise and Gaussian noise, which constitute the main noise appearing in the image. Experimental results show that the improvement visually enhanced image quality. Both peak signal-to-noise ratio (PSNR) and SSIM, which are quantitative indicators, show improved values.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.272-275
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• 2020

Light Field (LF) cameras capture both spatial and directional information of light rays. Current LF cameras have a problem of a low spatial resolution. There have been lots of existing works carried out to improve the resolution of LF images. In this paper, those existing works will be divided into two categories: hardware-based approaches and software-based approaches, and we will look into and compare several experiment results in order for LF spatial resolution enhancement. Finally, the direction for the future spatial resolution enhancement will be suggested.

• Journal of Biosystems Engineering
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• v.25 no.3
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• pp.213-220
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• 2000

Grafting of fruit-bearing vegetables has been widely used to increase the resistance to soil-borne diseases, to increase the tolerance to low temperature or to soil salinity, to increase the plant vigor, and to extend the duration of economic harvest time. After grafting, it is important to control the environment around grafted seedlings for the robust joining of a scion and rootstock. Usually the shading materials and plastic films are used to keep the high relative humidity and low light intensity in greenhouse or tunnel. It is quite difficult to optimally control the environment for healing and acclimation of grafted seedlings under natural light. So the farmers or growers rely on their experience for the production of grafted seedling with high quality. If artificial light is used as a lighting source for graft-taking of grafted seedlings, the light intensity and photoperiod can be easily controlled. The purpose of this study was to develop a prototype system for the graft-taking enhancement of grafted seedlings using artificial lighting and to investigate the effect of air current speed on the distribution of air temperature and relative humidity in a graft-taking enhancement system. A prototype graft-taking system was consisted by polyurethane panels, air-conditioning unit, system controller and lighting unit. Three band fluorescent lamps (FL20SEX-D/18, Kumho Electric, Inc.) were used as a lighting source. Anemometer (Climomaster 6521, KANOMAX), T-type thermocouples and humidity sensors (CHS-UPS, TDK) were used to measure the air current speed, air temperature and relative humidity in a graft-taking system. In this system, air flow acted as a driving force for the diffusion of heat and water vapor. Air current speed, air temperature and relative humidity controlled by a programmable logic controller (UP750, Yokogawa Electric Co) and an inverter (MOSCON-G3, SAMSUNG) had an even distribution. Distribution of air temperature and relative humidity in a graft-taking enhancement system was fairly affected by air current speed. Air current speed higher than 0.1m/s was required to obtain the even distribution of environmental factors in this system. At low air current speed of 0.1m/s, the evapotranspiration rate of grafted seedlings would be suppressed and thus graft-taking would be enhanced. This system could be used to investigate the effects of air temperature, relative humidity, air current speed and light intensity on the evaportranspiration rate of grafted seedlings.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.8-16
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• 2012

An image obtained from a low light environment results in a low-exposure problem caused by non-ideal camera settings, i.e. aperture size and shutter speed. Of particular note, the multiple color-filter aperture (MCA) system inherently suffers from low-exposure problems and performance degradation in its image classification and registration processes due to its finite size of the apertures. In this context, this paper presents a novel method for the color enhancement of low-exposure images and its application to color shift model-based MCA system for image refocusing. Although various histogram equalization (HE) approaches have been proposed, they tend to distort the color information of the processed image due to the range limits of the histogram. The proposed color enhancement algorithm enhances the global brightness by analyzing the basic cause of the low-exposure phenomenon, and then compensates for the contrast degradation artifacts by using an adaptive histogram specification. We also apply the proposed algorithm to the preprocessing step of the refocusing technique in the MCA system to enhance the color image. The experimental results confirm that the proposed method can enhance the contrast of any low-exposure color image acquired by a conventional camera, and is suitable for commercial low-cost, high-quality imaging devices, such as consumer-grade camcorders, real-time 3D reconstruction systems, digital, and computational cameras.

• Current Optics and Photonics
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• v.2 no.1
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• pp.85-89
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• 2018

This paper presents a new, efficient hybrid photonic-plasmonic structure. The proposed structure efficiently and with very high accuracy combines the resonant mode of a low-mode-volume photonic-crystal nanocavity with a bowtie nanoantenna's plasmonic resonance. The resulting enormous enhancement of light intensity of about $1.1{\times}10^7$ in the gap region of the bowtie nanoantenna, due to the effective optical-resonance combination, is realized by subtle optimization of the nanocavity's optical characteristics. This coupled structure holds great promise for many applications relying on strong confinement and enhancement of optical field in nanoscale volumes, including antennas (communication and information), optical trapping and manipulation, sensors, data storage, nonlinear optics, and lasers.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.1
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• pp.60-67
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• 2015

This paper proposes an image-dependent color image enhancement method that uses adaptive luminance enhancement and color emphasis. It effectively enhances details of low-light regions while maintaining well-balanced luminance and color information. To compare the structure similarity and naturalness, we used the tone mapped image quality index (TMQI). The proposed method maintained better structure similarity in the enhanced image than did the space-variant luminance map (SVLM) method or the adaptive and integrated neighborhood dependent approach for nonlinear enhancement (AINDANE). The proposed method required the smallest computation time among the three algorithms. The proposed method can be easily implemented using the field-programmable gate array (FPGA), with low hardware resources and with better performance in terms of similarity.