• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.68-74
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• 2017

This paper presents a joint demosaicking and arbitrary-ratio down sampling algorithm for color filter array (CFA) images. Color demosaiking is a necessary part of image signal processing pipeline for many types of digital image recording system using single sensor. Also, such as smart phone, obtained high resolution image from image sensor has to be down-sampled to be displayed on the screen. The conventional solution is "Demosaicking first and down sampling later". However, this scheme requires a significant amount of memory and computational cost. Also, artifacts can be introduced or details get damaged during demosaicking and down sampling process. In this paper, we propose a method in which demosaicking and down sampling are working simultaneously. We use inverse mapping of Bayer CFA and then joint demosaicking and down sampling with arbitrary-ratio scheme based on signal decomposition of high and low frequency component in input data. Experimental results show that our proposed algorithm has better image quality performance and much less computational cost than those of conventional solution.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.293-296
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• 2007

In this paper, we propose the systolic array architecture for the vector median filter. In the color image processing, the vector signal (i.e. the color) consists of three elements, red, green and blue. The vector median filter is very effective to utilize the correlation among red, green and blue elements. The computational complexity of the proposed architecture for computing the vector median of N vector signals is (N+2) clock periods compared to the (3N+1) clock periods in the previous method. In addition to, the input vector signals can be loaded in serial in the proposed architecture. In the previous method, N input vector signals should be loaded to the vector median filter in parallel at the first clock. The proposed architecture is implemented with FPGA.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.111-119
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• 2016

Most commercial digital cameras acquire the colors of an image through the color filter array, and interpolate missing pixels of the image. Because of this fact, original pixels and interpolated pixels have different statistical characteristics. If colors of an image are modified, the color filter array pattern that consists of RGB channels is changed. Using this pattern change, a color forgery detection method were presented. The conventional method uses the number of pixels that exceeds the maximum or minimum value of pre-defined block by only exploiting green component. However, this algorithm cannot remove the flat area which is occurred when color is changed. And the conventional method has demerit that cannot detect the forged image with rare green pixels. In this paper, we propose an enhanced color forgery detection algorithm using the normalization and weighted sum of the color components. Our method can reduce the detection error by using all color components and removing flat area. Through simulations, we observe that our proposed method shows better detection performance compared to the conventional method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1581-1588
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• 2010

Most digital cameras use a single image sensor with Color Filter Array(CFA) for the advantage of costs and speed. The various color interpolation(demosaicing) algorithms are researched to reconstruct a full representation of the image. In this paper, we proposed a method of demosaicing about using weighted directional filter for vertical, horizontal, and diagonal direction edge. The method considered the efficiency of hardware resources for hardware implementation. The performance of proposed method was confirmed by comparing the conventional method in experiments using 24 Kodak test images. The proposed method was designed by Verilog HDL and was verified by using Virtex4 FPGA boards and CMOS Image Sensor.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1216-1223
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• 2006

In many imaging devices, a single image sensor is used, which is covered by a color filter array to filter out the specific color components from light. Since an image acquired from this image sensors have a color components at each pixel, it is needed to be reconstructed to a perfect image. In this paper, a new color interpolation method for the imaging devices having a single image sensor is proposed. The proposed method improves a edge sensing function to obtain satisfactory results in edges of an image, md presents a new inter-channel correlation for improving interpolation performance in smooth region. We have compared our method with several exiting methods, and our experimental results have proved better interpolation performance in comparing with the other results.

• 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.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1741-1749
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• 2017

In commercial digital-cameras, color-filter filters light according to wavelength range of color filter array (CFA) and the filtered intensities contain color information of light. Then, output data of CFA is transformed to final rendered image through demosaicing process. In image processing of digital-camera, the quality of the final rendered image is affected by optical cross talk of CFA, kind of CFA pattern etc. Basically, pattern of CFA plays important role in image quality of final image rendered by digital-camera. Therefore, an evaluation system capable of quantitatively evaluating CFA is needed. This paper proposes a novel evaluation system using existing and proposed image metrics for evaluating CFAs of digital-camera. Proposed CFA evaluation system consist of color difference in CIELAB and S-CIELAB, Structure SImilarity (SSIM), MTF50, moire starting point (MSP), and subjective preference (SP). MSP and SP are newly designed for the proposed evaluation system. Proposed evaluation system is expressed in polar coordinates to analyze the characteristics of CFA objectively and intuitively. Through simulations, we confirmed that proposed CFA evaluation system can objectively assess performance of developed CFAs.