• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.211-218
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• 2002

This paper introduces the HD 3DTV camera and 3DTV receiver that are compatible with the ATSC HDTV broadcasting system. The developed 3DTV camera is based on stereoscopic techniques, and it has control function to control both left and right zoom lens simultaneously and to control the vergence. Moreover, in order to control the vergence manually and to eliminate the synchronization problem of the both images, the 3DTV camera has the 3DTV video multiplexing function to combine the left and right images into the single image. The developed 3DTV signal, and it has the various analog/digital interfaces. The performance of the developed system is confirmed by shooting the selected soccer game in 2002 FIFA KOREA/JAPANTM World Cup and by broadcasting the match. The HD 3DTV camera and receiver will be applied to the 3DTV industries such as 3D movie, 3D game, 3D image processing, 3DTV broadcasting system, and so on.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2011.07a
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• pp.399-402
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• 2011

카메라를 이용하여 정지 영상을 획득할 때 발생할 수 있는 모션 블러 (motion blur) 현상을 보정하기 위해서는 정확한 블러파라미터 (블러의 방향, 블러의 크기)의 추정이 가장 중요하다. 본 논문에서는 블러된 영상의 로그 스펙트럼 (log spectrum)의 비등방성 (anisotropic)과 엔트로피 (Entropy) 특성에 기반한 블러 파라미터 추정 방법을 제안한다. 제안하는 기법은 1D 로그스펙트럼을 이용한 비등방성의 효과적인 분석과 블러 크기의 정확도를 증가시키기 위한 보상 과정을 포함한다. 실험 결과를 통해 제안하는 기법이 단일 영상에서의 등속 직선 운동의 모션 블러 현상을 더 효과적으로 보정하는 것을 보였다.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.745-747
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• 2004

소실점은 실 공간의 평행한 직선들이 영상에서 만나는 점으로서 카메라 파라미터 추정. 영상을 사용한 3차원 구조복원 등에서 널리 사용되는 영상 상에 존재하는 3차원 기하에 대한 암묵적인 특징 정보이다. 본 논문에서는 영상으로부터 안정적으로 소실점을 검출하기 위한 새로운 방법을 제시한다. 먼저 단위구 상에서 셀 기반의 소실 공간을 EM 알고리즘의 초기 소실점으로 사용함한 신뢰성 있는 소실점 추출 방법을 제안한다. 또한 단일 영상에서 제거되지 않는 이상치에 대해 다중 영상에서 H응 직선이 가자는 사영불변치인 planar collineation과 harmonic range를 이용하여 보다 정확한 소실점을 구하기 위한 방법을 제안한다. 본 논문에서 제안한 알고리즘을 다양한 영상을 통해 실험한 결과 안정적이고 신뢰할만한 소실점 검출이 가능하였다.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.703-712
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• 2019

Single image Super-Resolution (SISR) aims to generate a visually pleasing high-resolution image from its degraded low-resolution measurement. In recent years, deep learning - based super - resolution methods have been actively researched and have shown more reliable and high performance. A typical method is WaveletSRNet, which restores high-resolution images through wavelet coefficient learning based on feature maps of images. However, there are two disadvantages in WaveletSRNet. One is a big processing time due to the complexity of the algorithm. The other is not to utilize feature maps efficiently when extracting input image's features. To improve this problems, we propose an efficient single image super resolution method, named RDB-WaveletSRNet. The proposed method uses the residual dense block to effectively extract low-resolution feature maps to improve single image super-resolution performance. We also adjust appropriated growth rates to solve complex computational problems. In addition, wavelet packet decomposition is used to obtain the wavelet coefficients according to the possibility of large scale ratio. In the experimental result on various images, we have proven that the proposed method has faster processing time and better image quality than the conventional methods. Experimental results have shown that the proposed method has better image quality by increasing 0.1813dB of PSNR and 1.17 times faster than the conventional method.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.47-55
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• 2012

In this paper, we propose a method to reconstruct accurate 3D shape object by using multi-view images which are disturbed by motion blur. In multi-view deblurring, more precise PSF estimation can be done by using the geometric relationship between multi-view images. The proposed method first estimates initial 2D PSFs from individual input images. Then 3D PSF candidates are projected on the input images one by one to find the best one which are mostly consistent with the initial 2D PSFs. 3D PSF consists with direction and density and it represents the 3D trajectory of object motion. 야to restore 3D shape by using multi-view images computes the similarity map and estimates the position of 3D point. The estimated 3D PSF is again projected to input images and they replaces the intial 2D PSFs which are finally used in image deblurring. Experimental result shows that the quality of image deblurring and 3D reconstruction improves significantly compared with the result when the input images are independently deblurred.

• Journal of Broadcast Engineering
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• v.15 no.2
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• pp.265-279
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• 2010

A color image requires at least three color channels to obtain the full color image. However the image sensor obtains only the intensity of the brightness, that is, three image sensors are required for every pixel to capture the full color image. Since the image sensor is quiet expensive, most of digital still cameras adopt single image sensor array with color filter array (CFA) to reduce the size and the cost. Since the image obtained using single sensor array has only one color component per pixel, we need to reconstruct the missing two color components to obtain the full color image. We call this process as color filter interpolation or demosaicking. In this paper, demosaicking algorithm composed of two large step is proposed. Proposed algorithm is combined with several different algorithms such as Edge-directed demosaicking, Second-order gradients as correction terms, Smooth hue transition Interpolation, etc. The simulation results show that the proposed algorithm performs much better than the state-of-the-art demosaicking algorithms in terms of both subjective and objective qualities.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.9
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• pp.22-30
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• 2011

Recently, the rising demand for intelligent video surveillance system leads to high-performance face recognition systems. The solution for low-resolution images acquired by a long-distance camera is required to overcome the distance limits of the existing face recognition systems. For that reason, this paper proposes a hardware design of an image resolution enhancement algorithm for real-time intelligent video surveillance systems. The algorithm is synthesizing a high-resolution face image from an input low-resolution image, with the help of a large collection of other high-resolution face images, called training set. When we checked the performance of the algorithm at 32bit RISC micro-processor, the entire operation took about 25 sec, which is inappropriate for real-time target applications. Based on the result, we implemented the hardware module and verified it using Xilinx Virtex-4 and ARM9-based embedded processor(S3C2440A). The designed hardware can complete the whole operation within 33 msec, so it can deal with 30 frames per second. We expect that the proposed hardware could be one of the solutions not only for real-time processing at the embedded environment, but also for an easy integration with existing face recognition system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.1004-1009
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• 2010

ost digital cameras use single sensor array with color filter array to reduce size and cost. However images taken by single sensor array have only one color component per pixel, to obtain a color image missing two color components need to be reconstructed. This reconstructing process is called as demosaicking. This paper propose a new directional demosaicking method and proposed method achieves better image quality with enhanced weighting function. With comparing objective and subjective performance, we show proposed method achieves better performance than the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12C
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• pp.1138-1146
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• 2009

Digital cameras adopting a single CCD detector collect image color by subsampling in three color planes and successively interpolating the information to reconstruct full-resolution color images. Therefore, to recovery of a full-resolution color image from a color filter array (CFA) like the Bayer pattern is generally considered as an interpolation issue for the unknown color components. In this paper, we first calculate luminance component value by combining R, G, B channel component information which is quite different from the conventional demosaicing algorithm. Because conventional system calculates G channel component followed by computing R and B channel components. Integrating the obtained gradient edge information and the improved weighting function in luminance component, a new edge sensitive demosaicing technique is presented. Based on 24 well known testing images, simulation results proved that our presented high-quality demosaicing technique shows the best image quality performance when compared with several recently presented techniques.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.92-100
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• 2006

In imaging devices such as digital cameras using a single image sensor, captured images are the sub-sampled images comprised of the pixels that have only one of the three primary colors per a pixel. This images should be restored to the color images through an image processing referred as color interpolation. In this paper, we derive relation between the average of the data from CFA image sensor and the average of each color channel data. By using this relation, a new efficient method for color interpolation is proposed. Also, in order to reduce the zipper effect in a restored image, missing luminance values are interpolated along any edges in the captured image. On the other hand, for the chrominance channel interpolation, we average difference between a chrominance value and a luminance value in a local area, and this average value is added to the pixel value of the interpolated location. The proposed method has been compared with several previous methods, and our experimental results show the better results than the other methods.