• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.407-419
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• 2006

In this paper, an adaptive illumination change compensation method is proposed for multi-view video coding. In multi-view video, an illumination change can occur due to physically imperfect camera calibration, each different camera position and direction, and so on. These characteristics can cause a performance decrease in the multi-view video coding that uses an inter-view prediction by referring to the pictures obtained from the neighboring views. By using the proposed method, a compression ratio of the proposed method in the multi-view video coding is increased, and finally $0.1{\sim}0.6dB$ PSNR(Peak Signal-to-Noise Ratio) improvement was obtained compared with the case of not using the proposed method.

• Journal of Broadcast Engineering
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• v.12 no.6
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• pp.565-573
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• 2007

In this paper, we propose a method to select motion vector predictor by considering prediction structure of a multi view content for coding efficiency of multi view coding which is being standardized in JVT. Motion vector of a different tendency is happened while carrying out temporal and view reference prediction of multi-view video coding. Also, due to the phenomena of motion vectors being searched in both temporal and view order, the motion vectors do not agree with each other resulting a decline in coding efficiency. This paper is about how the motion vector predictor are selected with information of prediction structure. By using the proposed method, a compression ratio of the proposed method in multi-view video coding is increased, and finally $0.03{\sim}0.1$ dB PSNR(Peak Signal-to-Noise Ratio) improvement was obtained compared with the case of JMVM 3.6 method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10B
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• pp.1428-1435
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• 2001

본 논문에서는 이미지 데이터의 저작권 보호를 위해 영상변형, JPEG 손실 압축 및 임펄스 잡음에 효과적인 새로운 DM/SS (Direct Matrix/Spread Spectrum) 이미지 워터마킹 기법을 제안한다. 제안하는 기법은 워터마크 영상을 저작권자의 개인 ID (IDentification)로 확산시킨 다음, 원 영상에 삽입하고 역확산시켜 복원하는 방법이다. 원터마크 영상은 2진 영상을 사용하고, 워터마크 시스템에서 요구되는 비가시성과 외부 공격에 대한 워터마크의 강인성을 확인하기 위하여 PSNR (Peak Signal to Noise Ratio)과 워터마크 영상의 복원율 (reconstructive rate)을 구한다. 실험 결과, 워터마크가 삽입된 영상의 PSNR은 93.75 dB로 화질저하가 거의 없었고, 확산 이득으로 인하여 32$\times$32 워터마크 영상이 삽입된 영상에서 우수한 워터마크 영상의 복원율을 얻는다는 것을 보인다. 영상변형 및 JPEG 손실 압축 하에서도 우수한 워터마크 복원 결과를 보였고, 임펄스 잡음이 첨가된 영상의 PSNR이 5.54 dB인 경우에도 효과적으로 워터마크 영상을 복원할 수 있다는 것을 알 수 있었다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.335-338
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• 2021

본 논문에서는 기존 AHDRNet에 channel attention 기법을 적용했을 때 성능에 어떠한 변화가 있는지를 평가하였다. 기존 모델의 병합 망에 존재하는 DRDB(Dilated Residual Dense Block) 사이, 그리고 DRDB 내의 확장된 합성곱 레이어 (dilated convolutional layer) 뒤에 또다른 합성곱 레이어를 추가하는 방식으로 channel attention 기법을 적용하였다. 데이터셋은 Kalantari의 데이터셋을 사용하였으며, PSNR(Peak Signal-to-Noise Ratio)로 비교해본 결과 기존의 AHDRNet의 PSNR은 42.1656이며, 제안된 모델의 PSNR은 42.8135로 더 높아진 것을 확인하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1189-1195
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• 2014

In this study we propose an image denoising algorithm which manipulates the information obtained from multiple images in the same environment for mobile smart phones. We also envisage a multiple images registration method for mobile smart phone cameras equipped with limited computing ability and present an effective image denoising algorithm combining and manipulating the information obtained from multiple images. We proved that the proposed algorithm has much better PSNR value than the method applying single image. We verified that the propose approach has good denoising quality and can be utilized in the feasible level speed on Android smart phones.

• Journal of the Korea Society of Computer and Information
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• v.12 no.3
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• pp.123-130
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• 2007

It is difficult to analyse images because of multiplicative characteristics of speckle noises in SAR images. In this paper. wavelet transform is proposed for restoring SAR images corrupted by speckle noise. The multiplicative noise is transformed into a form of additive noise and then the additive noise is denoised using wavelet thresholding selections such as VisuShrink, SureShrink, BayesShrink and modified BayesShrink. Experimental results on several test images show that the modified BayesShrink yields significantly superior image quality and better Peak Signal to Noise Ratio(PSNR).

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.43-53
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• 2001

WT(Wavelet Transform) is used to avoid blocking effect that is the disadvantage of JPEG using DCT(Discrete Cosine Transform). Because the proposed coding scheme is the same as JPEG, the proposed algorithm is compatible with that of JPEG. To achieve the goal, WT'ed image is reconstructed into 8$\times$8 coding block. Each coding block is quantized with the proposed weighting matrix that is derived from human visual characteristic and error analysis in WT'ed domain. By experiments, the proposed algorithm is superior to JPEG, in terms of PSNR(Peak Signal to Noise Ratio) and WMSE(Weighted Mean Square Error).

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.89-102
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• 2013

The paper presents a fuzzy based impulse noise filter for both gray scale and color images. The proposed approach is based on the technique of boundary discriminative noise detection. The algorithm is a multi-step process comprising detection, filtering and color correction stages. The detection procedure classifies the pixels as corrupted and uncorrupted by computing decision boundaries, which are fuzzified to improve the outputs obtained. In the case of color images, a correction term is added by examining the interactions between the color components for further improvement. Quantitative and qualitative analysis, performed on standard gray scale and color image, shows improved performance of the proposed technique over existing state-of-the-art algorithms in terms of Peak Signal to Noise Ratio (PSNR) and color difference metrics. The analysis proves the applicability of the proposed algorithm to random valued impulse noise.

• Journal of the Korean Society of Radiology
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• v.17 no.2
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• pp.191-199
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• 2023

This study aimed to propose minimized radiation doses with an optimized abdomen x-ray image, which realizes a Deep Blind Image Super-Resolution Generative adversarial network (BSRGAN) technique. Entrance surface doses (ESD) measured were collected by changing exposure conditions. In the identical exposures, abdominal images were acquired and were processed with the BSRGAN. The images reconstructed by the BSRGAN were compared to a reference image with 80 kVp and 320 mA, which was evaluated by mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). In addition, signal profile analysis was employed to validate the effect of the images reconstructed by the BSRGAN. The exposure conditions with the lowest MSE (about 0.285) were shown in 90 kVp, 125 mA and 100 kVp, 100 mA, which decreased the ESD in about 52 to 53% reduction), exhibiting PSNR = 37.694 and SSIM = 0.999. The signal intensity variations in the optimized conditions rather decreased than that of the reference image. This means that the optimized exposure conditions would obtain reasonable image quality with a substantial decrease of the radiation dose, indicating it could sufficiently reflect the concept of As Low As Reasonably Achievable (ALARA) as the principle of radiation protection.