• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.242-245
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• 2000

In this paper, we present a color interpolation technique based on artificial neural networks for a single-chip CCD (charge-coupled device) camera with a Bayer color filter array (CFA). Single-chip digital cameras use a color filter array and an interpolation method in order to regenerate high quality color images from sparsely sampled images. We applied 3-layer feedforward neural networks in order to interpolate missing pixel from surrounding pixels. And we compared the proposed method with conventional interpolation methods such as the proposed interpolation algorithm based on neural networks provides a better performance than the conventional interpolation algorithms.

• 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.

• ETRI Journal
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• v.38 no.1
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• pp.164-173
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• 2016

Demosaicing, or color filter array (CFA) interpolation, estimates missing color channels of raw mosaiced images from a CFA to reproduce full-color images. It is an essential process for single-sensor digital cameras with CFAs. In this paper, a new demosaicing method for digital cameras with Bayer-like W-RGB CFAs is proposed. To preserve the edge structure when reproducing full-color images, we propose an edge direction-adaptive method using color difference estimation between different channels, which can be applied to practical digital camera use. To evaluate the performance of the proposed method in terms of CPSNR, FSIM, and S-CIELAB color distance measures, we perform simulations on sets of mosaiced images captured by an actual prototype digital camera with a Bayer-like W-RGB CFA. The simulation results show that the proposed method demosaics better than a conventional one by approximately +22.4% CPSNR, +0.9% FSIM, and +36.7% S-CIELAB distance.

• 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.

• 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.

• 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.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 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 Broadcast Engineering
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• v.14 no.6
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• pp.742-748
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• 2009

Most commercial digital still cameras use a single sensor array (e.g., CMOS or CCD) with color filter array (CFA) to reduce the cost and size. Since the image obtained with CFA has only one color value per pixel, the demosaicing is needed to acquire missing two color values. Although many demosaicing methods have been proposed, they still have artifacts such as rainbow and zippering artifact. In this paper, we propose the simple demosaicing algorithm using tendency of neighbor pixels with the enhanced weighting function. In the experimental results, our algorithm shows much better subjective qualities of the images than conventional demosaicing algorithm and improves objective qualities.

• 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.