• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.39-44
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• 2004

The three-dimensional (3D) wavelet transform with motion compensation is suitable for very high quality video coding due to both spatial and temporal decorrelations. However, it still suffers from image degradation such as ringing artifact and afterimage because of the loss of high frequency components by quantization. This paper proposes an iterative regularized enhancement of the motion-compensated 3D wavelet coded video. We also propose the adaptive implementation of the constraints for the regularization. It selectively suppresses the high frequency component along only the corresponding edge direction.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.316-320
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• 2009

In this paper, a reference-free perceptual quality metric is proposed for image assessment. It measures the amount of overall blockiness and blurring in the image. And edge-oriented artifacts, such as ringing, mosaic and staircase noise are also considered. In order to give a single quality score, the individual artifact scores are adaptively combined according to the difference between the edge-oriented artifacts and other artifacts. The quality score obtained by the proposed algorithm shows strong correlation with the MOS values by VQEG.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.107-112
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• 1997

This paper proposes the regularized constrained iterative image restoration algorithms which apply new space-adaptive methods to degraded image signals, and analyzes the convergence condition of the proposed algorithm. First, we introduce space-adaptive regularization operators which change according to edge characteristics of local images in order to effectively prevent the restored edges and boundaries from reblurring. And, pseudo projection operator is used to reduce the ringing artifact which results from extensive amplification of noise components in the restoration process. The analysed algorithm is stable convergent to the fixed point. According to the experimental results for various signal-to-noise ratios(SNR) and blur models, the proposed algorithms other methods and is robust to noise effects and edge reblurring by regularization especially.

• Journal of Korea Multimedia Society
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• v.25 no.1
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• pp.29-38
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• 2022

Although image compression is one of the essential technologies to transmit image data on a variety of surveillance and mobile healthcare applications, it causes unnecessary compression artifacts such as blocking and ringing artifacts by the lossy compression in the limited network bandwidth. Recently, image restoration methods using convolutional neural network (CNN) show the significant improvement of image quality from the compressed images. In this paper, we propose Image Denoising Convolutional Neural Networks (IDCNN) to reduce the compression artifacts for the purpose of improving the performance of object classification. In order to evaluate the classification accuracy, we used the ImageNet test dataset consisting of 50,000 natural images and measured the classification performance in terms of Top-1 and Top-5 accuracy. Experimental results show that the proposed IDCNN can improve Top-1 and Top-5 accuracy as high as 2.46% and 2.42%, respectively.

• Journal of Biomedical Engineering Research
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• v.33 no.2
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• pp.72-77
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• 2012

Phase Contrast MR Angiography(PC MRA) is excellent MRA technique for measuring the velocity of vessels in the human body. PC MRA need to at least four images for angiogram reconstruction and it caused longer scan time. Therefore, we used keyhole imaging combined PC MRA to reduce the scan time. However, keyhole imaging can lead the erroneous effects as loss of phase information or frequency discontinuous. In this study, we applied the keyhole imaging combined 2D PC MRA for improving the temporal resolution and also measured the velocity to evaluate the accuracy of phase information. We used 0.32T MRI scanner(Magfinder II, Scimedix, Korea). Using the 2D PC MRA pulse sequence, the vascular images for a human brain targeted on the Superior Sagittal Sinus(SSS) were obtained. We applied tukey window function for keyhole images to minimize the ringing artifact and erroneous factors that are induced frequency discontinuous and phase information loss. We also applied zero-padded algorithm to peripheral missing k-space lines to compare keyhole imaging results and the artifact power(AP) value was measured on the complex difference images to validate the image quality. Consider as based on our results, heavy image distortions and artifacts were shown until using at least 50% keyhole factor. Using above the 50% keyhole factors are shown well reconstructed and matched for magnitude images and velocity information measurements. In conclusion, we confirmed the image quality and velocity information of keyhole technique combined 2D PC MRA. Especially, measured velocity information through the keyhole imaging combination was similar to the velocity information of full sampled k-space image despite of frequency discontinuous and phase information loss in the keyhole imaging reconstruction process. Consequently, the keyhole imaging combined 2D PC MRA will give some clinical usefulness and advantages as improving the temporal resolution and measuring the velocity information via selecting the appropriate keyhole factor at low tesla MRI system.