• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.171-173
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• 2000

In this paper, we present a new interpolation method for the color filter away(CFA). In order to capture color images. typical input devices use a single chip CCD imaging sensor with color filter array. As a result, the single chip CCD does not provide sufficient color resolutions since it arranges different color filters sequentially on a single CCD, resulting in aliasing noise and loss of resolution. In order to reconstruct high quality color images, we propose to use the interpolation algorithm using high order B-splines. Experiments show promising results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.62-70
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• 2011

Nowadays image sensor is an essential component in many multimedia devices, and it is covered by a color filter array to filter out specific color components at each pixel. We need a certain algorithm to combine those color components reconstructed a full color image from incomplete color samples output from an image sensor, which is called a demosaicking process. Most existing demosaicking algorithms are developed for ideal image sensors, but they do not work well for the practical cases because of dissimilar characteristics of each sensor. In this paper, we propose a new demosaicking algorithm in which the color filter characteristics are fully utilized to generate a good image. To demonstrate significance of our algorithm, we used a commerically available sensor, CBN385B, which is a sort of Honeycomb-style CFA(Color Filter Array) CCD image sensor. As a performance metric of the algorithm, PSNR(Peak Signal to Noise Ratio) and RGB distribution of the output image are used. We first implemented our algorithm in C-language for simulation on various input images. As a result, we could obtain much enhanced images whose PSNR was improved by 4~8 dB compared to the commonly idealized approaches, and we also could remove the inclined red property which was an unique characteristics of the image sensor(CBN385B).Then we implemented it in hardware to overcome its problem of computational complexity which made it operate slow in software. The hardware was verified on Spartan-3E FPGA(Field Programable Gate Array) to give almost the same performance as software, but in much faster execution time. The total logic gate count is 45K, and it handles 25 image frmaes per second.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5C
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• pp.286-294
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• 2011

In most digital cameras, images are obtained by a sensor overlaid by the color filter array (CFA) such as Bayer, demanding a demosaicking procedure to rebuild the full resolution color images. However, due to the nature of sensor, it is necessary to consider denoising step to remove the noise. In this paper, we analyze demosaicking and denoising jointly and show that the proposed method can solve the denoising issue by simple manner, well suppress different level of noises. The proposed algorithm yields comparable performances measured by several image quality assessment (CPSNR, SCIELAB, and FSIM), while the computational cost is low.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.53-61
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• 2010

In this paper, we present a color interpolation algorithm that uses novel edge direction estimator and region classifier. The proposed edge direction estimator accurately determines the edge direction based on the correlation between the images obtained by the channel separated and down-sampled Bayer color filter array(CFA) pattern. The correlation is defined based on the similarity between the edge direction in the local region of the image and the shifting direction of the images. Also, the region of an image is defined as the flat, the edge, and the pattern-edge regions, where the edges are appeared repeatedly. When all the pixels in the image are classified into the three different regions, each pixel is interpolated horizontally or vertically according to the estimated direction. Experimental results show that the proposed algorithm outperforms the conventional edge-directed methods on objective and subjective criteria.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.59-70
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• 2010

Each pixels become got pixel value for color of only one from among colors because of bayer pattern that light receiving device of image sensor which is used in HHP and digital camera writes only one color. Information of the missing pixels could infer perfect color image from using information of neighbor pixels by using CFA(Color Filter Array). In this paper, we derive relation between the average of the data from the light receiving device of image sensor and each color channel data. And by using this relation, a new efficient edge color fuzzy method for color interpolation is proposed. Also, missing luminance signal channel interpolation was fuzzy interpolation along any edges direction for reducing color noise and interpolating efficiently it. And in this paper, the proposed method has been proved improving average 2.4dB than the conventional method by using PSNR. Also, resolution of the image of the proposed method was similar to the original image by visual images, we has been verified to be decreased a chromatic aberration than image of conventional algorithms with simulation result.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1118-1121
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• 2010

With the advent of cell phone digital cameras, and sophisticated photo editing software, digital images can be easily manipulated and altered. Although good forgeries may leave no visual clues of having been tampered with, they may, nevertheless, alter the underlying statistics of an image. Most digital camera equipped in cell phones employ a single image sensor in conjunction with a color filter array (CFA), and then interpolates the missing color samples to obtain a three channel color image. This interpolation introduces specific correlations which are likely to be destroyed when tampering with an image. We quantify the specific correlations introduced by CFA interpolation, and describe how these correlations, or lack thereof, can be automatically detected in any portion of an image. We show the efficacy of this approach in revealing traces of digital tampering in lossless and lossy compressed color images interpolated with several different CFA algorithms in test cell phones.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.205-207
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• 2009

디지털 카메라를 이용한 영상 취득은 일반적으로 한 픽셀에서 세 가지 색상(적색, 녹색, 청색)의 값을 얻는 것을 목표로 한다. 하지만, 비용의 문제로 한 픽셀에서 한 가지의 색상만을 얻어 나머지 두 색상을 복원하는 방식을 널리 사용한다. 이를 demosaicking이라 하는데, 이 과정에는 1)각 색상 영상 내의 상관관계와 2)세 가지 색상 사이의 상관관계가 동시에 이용된다. 본 논문에서는 이 두 가지 상관관계를 이용하여 각 채널의 고주파 성분과 밝기 성분의 고주파 성분을 반복적으로 향상시키는 방법을 제안하였다. 첫 번째 단계에서는 밝기 성분을 이용하여 각 채널의 고주파 성분을 강화하고, 두 번째 단계에서 관측값을 이용하여 밝기 성분의 고주파 성분을 복원한다. 제안된 방법이 기존 방법과 주관적인 방법과 객관적인 방법으로 비교하여 우수함을 보인다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.656-659
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• 2012

In general, images captured by the color filter array are compressed after applying demosaicking process. Since this process introduces data redundancy which can reduce coding efficiency, several methods have been proposed to address this problem. While some conventional approachs convert color format to GBR or YUV 4:2:2 format, we propose to use the YCoCg 4:2:2 format to carry out compression. The proposed method shows an average bits reduction of 3.91% and PSNR increase of 0.04dB compared with H.264 YUV 4:2:0 intra-profile prediction method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.110-116
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• 2017

This paper presents an effective demosaicking algorithm for color filter array (CFA) images acquired from single-sensor devices based on directional interpolation and nonlocal properties of the image. We interpolate the G channel considering diagonal directions as well as horizontal and vertical directions, using a small number of pixels to reflect local properties of the image. Then, we overcome image degradations, such as zipper effects near edges and false colors, by applying nonlocal means (NLM) filtering to the interpolated pixels. R and B channels are reproduced by using directional interpolation with information of the reconstructed G channel and NLM filtering. Experimental results for various McMaster images with high saturation and color changes show that the proposed algorithm accomplishes high PSNR compared with conventional methods. Moreover, the proposed method demonstrates better subjective quality compared with existing methods in terms of reduction of quality degradation, like false colors, and preservation of the image structures, such as edges and textures.