• Title/Summary/Keyword: color filter array

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Expanded Exit-Pupil Holographic Head-Mounted Display With High-Speed Digital Micromirror Device

  • Kim, Mugeon;Lim, Sungjin;Choi, Geunseop;Kim, Youngmin;Kim, Hwi;Hahn, Joonku
    • ETRI Journal
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    • v.40 no.3
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    • pp.366-375
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    • 2018
  • Recently, techniques involving head-mounted displays (HMDs) have attracted much attention from academia and industry owing to the increased demand for virtual reality and augmented reality applications. Because HMDs are positioned near to users' eyes, it is important to solve the accommodation-vergence conflict problem to prevent dizziness. Therefore, holography is considered ideal for implementing HMDs. However, within the Nyquist region, the accommodation effect is limited by the space-bandwidth-product of the signal, which is determined by the sampling number of spatial light modulators. In addition, information about the angular spectrum is duplicated over the Fourier domain, and it is necessary to filter out the redundancy. The size of the exit-pupil of the HMD is limited by the Nyquist sampling theory. We newly propose a holographic HMD with an expanded exit-pupil over the Nyquist region by using the time-multiplexing method, and the accommodation effect is enhanced. We realize time-multiplexing by synchronizing a high-speed digital micromirror device and a liquid-crystal shutter array. We also demonstrate the accommodation effect experimentally.

Noise reduction Algorithm for CFA Images (컬러 필터 배열 영상에서의 잡음제거 알고리즘)

  • Lee, Min-Seok;Park, Sang-Wook;Kwon, Ji-Yong;Kang, Moon-Gi
    • 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.

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Analysis on the new McMaster image dataset to develop demosaicking techniques (디모자익킹 기술 개발을 위한 신규 맥매스터 영상 데이터에 대한 해석)

  • Yoo, Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.2
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    • pp.344-349
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    • 2012
  • This paper describes experimental results and their analysis on the new test images, called as the McMaster image dataset, to develop demosaicking techniques. The well-known image dataset for demosaicking is so far the Kodak image dataset. However, different results have been reported, as the new image dataset is engaged in developing demosaicking techniques. Thus, we conduct a series of experiments on both the McMaster dataset and the Kodak dataset; we analyze and compare those experimental results; and we provide the peculiar features of the new dataset. Also, the experimental results and their analysis indicate that the McMaster dataset deserves to be a test image dataset for future demosaicking techniques; thus, we expect they can be utilized as basic data for demosaicking.

Classifier Combination Based Source Identification for Cell Phone Images

  • Wang, Bo;Tan, Yue;Zhao, Meijuan;Guo, Yanqing;Kong, Xiangwei
    • 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.

Comparative Analysis of Color Filter Array Patterns for Single Sensor Digital (싱글 센서 디지털 카메라를 위한 CFA의 다양한 패턴 비교 분석)

  • Seo, Kyunghee;Yoo, Hoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.189-192
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    • 2009
  • This paper presents comparison and analysis of various CFA patterns which are used in single sensor digital camera. There are several patterns which are already used, however, images are sometimes darker or brighter than what human see in real life. Also, images show some noise and blurring. To overcome this problems, many studies on the patterns have been discussed. We carry out experiment with seven patterns including the Bayer pattern. The bilinear method is selected for a interpolation method. The experimental result indicates that image quality is not affected by individual patterns and each pattern requires its own interpolation method.

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