• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.105-110
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• 2016

To reduce the cost and volume of a digital camera, a subsampled color filter array(CFA) image is used and demosaicking is applied to estimate the missing color values. However, aliasing, the overlaps of signals in the frequency domain, occurs when signals are subsampled. This causes aliasing artifacts such as false colors and zipper effects in demosaicking processes. In this paper, the algorithm estimating high-quality color images by removing aliasing artifacts in them is proposed. The aliasing region map is estimated using the sub-sampled signals of the CFA image. By using the aliasing region map and the estimated luminance image, the least squares problem of the observation models is designed and aliasing artifacts are eliminated. The experiments demonstrate that the proposed algorithm restores color images without aliasing artifacts.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.413-414
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• 2007

본 논문은 칼라 필터 배열(color filter array : CFA) 영상에서 채널 간 상관관계를 이용한 새로운 에지 방향 컬러 보간 방법을 제시하였다. 고정 채널 간 컬러 차 가정에 따라 휘도와 색차간의 차가 큰 경우 에지 영역이라 판단한다. 에지 방향 판별을 정확히 하기 위해 수평, 수직 방향으로 컬러 차 영상을 구하고, 구한 영상에서 변화량을 계산하여 에지 방향 판별 기준으로 사용한다. 에지 판별 기준을 사용하여, 에지 방향에 따라 컬러 보간을 수행한다. 평탄 영역은 이웃 화소와의 유사성에 따라 가중치를 다르게 줘서, 이웃 화소의 가중치 합으로 구한다 실험 결과는 제안하는 알고리즘이 기존 알고리즘 보다 우수함을 보여준다.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.129-138
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• 2014

Various interpolations for digital imaging devices with a single image sensor have proposed. However, conventional methods did not consider the resolution modus of image sensor using periodic sampling. Therefore, the resulting images have problems such as quality degradation and color artifacts(color moire, zipper). In this paper, we propose a color interpolation algorithm for pixel resolution modus of image sensor. The proposed algorithm consisted of an initial step to compensate edge prediction effectively and refinement step using minimum directions for pixel resolution modus. To analyze a result of the proposed algorithm with conventional methods, we evaluated subjectively using images quality comparison and objectively using PSNR(Peak Signal to Noise Ratio). Experimental results showed that the proposed algorithm was more successful in eliminating the color artifacts than conventional methods judged by both objective and subjective criteria.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.619-630
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• 2013

In this paper, we propose an edge directed color demosaicing algorithm considering color channel correlation. The proposed method consists of local region classification step and edge directional interpolation step. In the first step, each region of a given Bayer image is classified as normal edge, pattern edge, and flat regions by using intra channel and inter channel gradients. Especially, two criteria and verification process for the normal edge and pattern edge classification are used to reduce edge direction estimation error, respectively. In the second step, edge directional interpolation process is performed according to characteristics of the classified regions. For horizontal and vertical directional interpolations, missing color components are obtained from interpolation equations based on intra channel and inter channel correlations in order to improve the performance of the directional interpolations. The simulation results show that the proposed algorithm outperforms conventional approaches in both objective and subjective terms.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.67-69
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• 2010

대부분의 디지털 카메라는 컬러 필터 배열(Color Filter Array)을 가진 하나의 영상 획득 센서를 사용한다. 따라서 영상획득 이후에 컬러 보간 알고리즘이 필수적으로 진행된다. 또 영상 획득 과정에서 센서의 열화나 암전류 등과 같은 잡음이 발생하여 영상 잡음 제거 알고리즘이 필요하다. 하지만 기존의 대부분의 영상 잡음 제거 알고리즘은 컬러 필터 배열 영상의 특징인 모자이크 데이터 기반이 아닌 컬러 보간 이후의 풀 컬러영상에(YCbCr) 적용되고 있다. 따라서 잡음이 포함된 영상으로 컬러 보간을 할 경우 잡음의 공간적 상관관계(spatial correlation)가 커짐에 의한 잡음 번짐 때문에 컬러 보간 이후의 잡음제거는 더욱 어렵게 된다. 이와 같은 문제를 해결하기 위해 컬러 필터 배열 영상에 대한 잡음제거 알고리즘이 연구되고 있으며, 본 논문에서도 CMOS/CCD의 이미지 센서에서 획득된 베이어 컬러 필터 배열 영상에서 잡음을 제거하는 알고리즘을 제안한다. 이를 위해서 베이어 컬러 필터 배열 영상 데이터에서 경계(edge)의 방향성을 고려한 LMMSE 방법을 기반으로 한 잡음제거 알고리즘을 제안한다. 제안하는 알고리즘은 영상의 경계를 보존해주며 잡음제거 과정 다음에 진행되는 컬러 보간 과정에서의 잡음 번짐의 문제를 해결할 수 있다. 실험 결과를 통해 향상된 잡음 제거 효과를 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5087-5102
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• 2015

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.205-215
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• 2013

In digital imaging system, Bayer pattern is widely used and the observed image is degraded by optical blur during image acquisition process. Generally, demosaicing and deblurring process are separately performed in order to convert a blurred Bayer image to a high resolution color image. However, the demosaicing process often generates visible artifacts such as zipper effect and Moire artifacts when performing interpolation across edge direction in Bayer pattern image. These artifacts are emphasized by the deblurring process. In order to solve this problem, this paper proposes a deblurring algorithm combined with edge directional color demosaicing method. The proposed method is consisted of interpolation step and region classification step. Interpolation and deblurring are simultaneously performed according to horizontal and vertical directions, respectively during the interpolation step. In the region classification step, characteristics of local regions are determined at each pixel position and the directionally obtained values are region adaptively fused. Also, the proposed method uses blur model based on wave optics and deblurring filter is calculated by using estimated characteristics of local regions. The simulation results show that the proposed deblurring algorithm prevents the boosting of artifacts and outperforms conventional approaches in both objective and subjective terms.