• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.73-80
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• 2019

In this paper, we propose an effective dynamic range compression (DRC) method of infrared images. A histogram of infrared images has narrow dynamic range compared to visible images. Hence, it is important to apply the effective DRC algorithm for high performance of an infrared image analysis. The proposed algorithm for high dynamic range divides an infrared image into the overlapped blocks and calculates Shannon's entropy of overlapped blocks. After that, we classify each block according to the value of entropy and apply adaptive histogram modification method each overlapped block. We make an intensity mapping function through result of the adaptive histogram modification method which is using standard-deviation and maximum value of histogram of classified blocks. Lastly, in order to reduce block artifact, we apply hanning window to the overlapped blocks. In experimental result, the proposed method showed better performance of dynamic range compression compared to previous algorithms.

• Journal of IKEEE
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• v.26 no.2
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• pp.292-298
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• 2022

There is a limit to improving the image quality through global processing of images taken under backlighting because too bright and dark parts are mixed in one scene. This paper introduces a method to improve the quality of a photo by making two virtual images that improve the dark and bright areas of a backlit photo, and fusing them with the original image into a Laplacian pyramid. The proposed method reduces the computational burden by using histogram stretching and gamma transformation that can be simplified with LUT when creating the two virtual images. In addition, in order to obtain a color-enhanced image, contrast conversion was performed only on the luminance using the HSV coordinate system. The proposed technique showed its effectiveness by calculating several NIQA indicators using standard image data sets.

• 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.

• Analytical Science and Technology
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• v.35 no.1
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• pp.1-7
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• 2022

This study suggests a new one-step fluorescent cyanoacylate-fuming method for developing fingerprints by using a CAB mixed with dimethylaminobenzalde (DMAB) and cyanoacylate (CA) in a specific ratio. CAB is prepared by mixing 2.5 % (w/w) DMAB with CA and fumigated at 180 ℃. Under these conditions, developing fingerprints showed the best results. The fuming method using CAB develops latent fingerprints into fluorescence and has a higher sensitivity than CA, and it showed comparable or better contrast to existing fluorescence enhancement methods. It was also applicable on a variety of non-porous surfaces that can be encountered at ordinary times. This method is more useful than conventional fluorescent dyeing methods in that it minimizes damage to fingerprints or samples, makes it easy to manufacture, saves time, and can use existing current equipment as it is.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5998-6016
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• 2017

In thin-film transistor liquid-crystal displays (TFT-LCDs), which are most commonly used in mobile devices, the backlight accounts for about 70% of the power consumption. Therefore, most low-power-related studies focus on realizing power savings through backlight dimming. Image compensation is performed to mitigate the visual distortion caused by the backlight dimming. Therefore, popular techniques include pixel compensation for brightness recovery and contrast enhancement, such as histogram equalization. However, existing pixel compensation techniques often have limitations with respect to blur owing to the pixel saturation phenomenon, or because contrast enhancement cannot adequately satisfy the human visual system (HVS). To overcome these, in this study, we propose a novel dimming technique to achieve both power saving and HVS-awareness by combining the pixel compensation and histogram specifications, which convert the original cumulative density function (CDF) by designing and using the desired CDF of an image. Because the process of obtaining the desired CDF is customized to consider image characteristics, histogram specification is found to achieve better HVS-awareness than histogram equalization. For the experiments, we employ the LIVE image database, and we use the structural similarity (SSIM) index to measure the degree of visual satisfaction. The experimental results show that the proposed technique achieves up to 15.9% increase in the SSIM index compared with existing dimming techniques that use pixel compensation and histogram equalization in the case of the same low-power ratio. Further, the results indicate that it achieves improved HVS-awareness and increased power saving concurrently compared with previous techniques.

• Analytical Science and Technology
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• v.36 no.3
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• pp.121-127
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• 2023

The detection of blood at a crime scene is an important process for identification and case reconstruction. However, blood may be difficult to observe with the naked eye on dark or multi-colored surfaces. Acidic hydrogen peroxide (AHP) is a recently reported blood enhancement reagent that can enhance blood with high sensitivity by increasing the exposure time of the camera. However, it has never been compared to previously known techniques on dark or multi-colored surfaces. For this purpose, the method of observation/photographing (UV and IR photography), alginate casting, leuco rhodamine 6G (LR6G), and AHP were applied to bloody impression on dark or multi-colored surfaces and the results were compared. As a result, blood treated with AHP had a higher contrast to the surfaces than UV and IR photography, and it was applicable on all surfaces, opposed to alginate casting. In addition, AHP successfully enhanced blood on dark or multi-colored surfaces, similar to LR6G.

• Imaging Science in Dentistry
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• v.45 no.2
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• pp.81-87
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• 2015

Purpose: Contrast, sharpness, enhancement, and density can be changed in digital systems. The important question is to what extent the changes in these variables affect the accuracy of caries detection. Materials and Methods: Forty eight extracted human posterior teeth with healthy or proximal caries surfaces were imaged using a photostimulable phosphor (PSP) sensor. All original images were processed using a six-step method: (1) applying "Sharpening 2" and "Noise Reduction" processing options to the original images; (2) applying the "Magnification 1:3" option to the image obtained in the first step; (3) enhancing the original images by using the "Diagonal/"option; (4) reviewing the changes brought about by the third step of image processing and then, applying "Magnification 1:3"; (5) applying "Sharpening UM" to the original images; and (6) analyzing the changes brought about by the fifth step of image processing, and finally, applying "Magnification 1:3." Three observers evaluated the images. The tooth sections were evaluated histologically as the gold standard. The diagnostic accuracy of the observers was compared using a chi-squared test. Results: The accuracy levels irrespective of the image processing method ranged from weak (18.8%) to intermediate (54.2%), but the highest accuracy was achieved at the sixth image processing step. The overall diagnostic accuracy level showed a statistically significant difference (p=0.0001). Conclusion: This study shows that the application of "Sharpening UM" along with the "Magnification 1:3" processing option improved the diagnostic accuracy and the observer agreement more effectively than the other processing procedures.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.61-73
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• 2012

This paper proposes a histogram specification based image enhancement method, which uses the brightness mean and variance of an image to maximize the entropy of the image. In our histogram specification step, the Gaussian distribution is used to fit the input histogram as well as produce the target histogram. Specifically, the input histogram is fitted with the Gaussian distribution whose mean and variance are equal to the brightness mean(${\mu}$) and variance(${\sigma}2$) of the input image, respectively; and the target Gaussian distribution also has the mean of the value ${\mu}$, but takes as the variance the value which is determined such that the output image has the maximum entropy. Experimental results show that compared to the existing methods, the proposed method preserves the mean brightness well and generates more natural looking images.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.56-63
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• 2012

In this paper, adaptive unsharp masking using bilateral filter, edge-preserving smoothing filter is proposed to reduce the overshoot and jagging artifact in sharpening images. Previous image enhancement methods including unsharp masking(UM) can emphasize high-frequency details strongly, but often cause several artifacts such as overshooting, noise, jagging and so on. Proposed image enhancement method preserves edges well because of using bilateral filter and sensitively controls a weight according to edge's directions. Therefore, it enhances sharpness and effectively reduces overshoot and jagging artifacts. Simulation results comparing output of previous AUM with proposed method show that proposed algorithm makes images properly enhanced, and we know that overshoot and jagging artifacts are many reduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1814-1828
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• 2021

Low-light image enhancement is a key technique to overcome the quality degradation of photos taken under scotopic vision illumination conditions. The degradation includes low brightness, low contrast, and outstanding noise, which would seriously affect the vision of the human eye recognition ability and subsequent image processing. In this paper, we propose an approach based on deep learning and Retinex theory to enhance the low-light image, which includes image decomposition, illumination prediction, image reconstruction, and image optimization. The first three parts can reconstruct the enhanced image that suffers from low-resolution. To reduce the noise of the enhanced image and improve the image quality, a super-resolution algorithm based on the Laplacian pyramid network is introduced to optimize the image. The Laplacian pyramid network can improve the resolution of the enhanced image through multiple feature extraction and deconvolution operations. Furthermore, a combination loss function is explored in the network training stage to improve the efficiency of the algorithm. Extensive experiments and comprehensive evaluations demonstrate the strength of the proposed method, the result is closer to the real-world scene in lightness, color, and details. Besides, experiments also demonstrate that the proposed method with the single low-light image can achieve the same effect as multi-exposure image fusion algorithm and no ghost is introduced.