• Title/Summary/Keyword: Demosaicking

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Color Image Restoration in Detected Aliasing Region (에일리어싱 영역 검출을 통한 컬러 영상 복원)

  • Kwon, Ji Yong;Kang, Moon Gi
    • 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.

DCT Methods for Demosaicking of Bayer-Sampled Color Images (이산여현변환을 이용한 베이어 패턴 디모자이킹 알고리듬)

  • Shin, Hyejin;Jeon, Gwanggil;Jeong, Je-Chang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2012.07a
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    • pp.59-62
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    • 2012
  • 본 논문에서는 이산 코사인 변환한 결과를 기반으로 필터링을 통해 디모자이킹 하는 알고리듬을 제안한다. 이산 코사인 변환한 결과로 에너지가 에지방향의 정보를 나타내는 분포 특성을 활용하여 가중치를 부여할 수 있는 효율적인 방법을 제안하고 이를 통해 필터링 하는 방법을 제안한다. 실험결과에서는 기존의 양선형 보간법에 비해 PSNR 측면에서의 뛰어난 성능을 보여준다.

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A Study on demosaicking using DCGAN (DCGAN을 활용한 디모자이킹에 관한 연구)

  • Jang, Young-chae;Anisetti, Macro;Jeon, Gwanggil
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.792-794
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    • 2018
  • 본 연구에서는 일반적으로 R,G,B 색 평면의 높은 상관관계를 이용하여 컬러 복원을 시도하던 기존의 방법의 문제점을 정의하고, DCGAN을 활용한 디모자이킹에 관한 연구를 소개한다. 약 2000장의 $256{\times}256$ 이미지를 학습데이터를 이용하였다. 보다 나은 결과를 위하여 R,G,B 색상 채널에 따라 각각의 네트워크를 구성하고 학습하였다. 제안 방법은 Intel Core i7-7770 CPU(3.60GHz), 16GB Memory,NVIDIA GeForce GTX1080Ti 구성의 Laptop에서 진행하였고, 평균 PSNR 22.5dB 정도의 성능을 보인다.

Edge Adaptive Color Interpolation for Ultra-Small HD-Grade CMOS Video Sensor in Camera Phones

  • Jang, Won-Woo;Kim, Joo-Hyun;Yang, Hoon-Gee;Lee, Gi-Dong;Kang, Bong-Soon
    • Journal of information and communication convergence engineering
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    • v.8 no.1
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    • pp.51-58
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    • 2010
  • This paper proposes an edge adaptive color interpolation for an ultra-small HD-grade complementary metal-oxide semiconductor (CMOS) video sensor in camera phones that can process 720-p/30-fps videos. Recently, proposed methods with great image quality perceptually reconstruct the green component and then estimate the red/blue component using the reconstructed green and neighbor red and blue pixels. However, these methods require the bulky memory line buffers in order to temporally store the reconstructed green components. The edge adaptive color interpolation method uses seven or nine patterns to calculate the six edge directions. At the same time, the threshold values are adaptively adjusted by the sum of the color values of the selected pixels. This method selects the suitable one among the patterns using two flowcharts proposed in this paper, and then interpolates the missing color values. For verification, we calculated the peak-signal-to-noise-ratio (PSNR) in the test images, which were processed by the proposed algorithm, and compared the calculated PSNR of the existing methods. The proposed color interpolation is also fabricated with the 0.18-${\mu}m$ CMOS flash memory process.

Demosaicing based Image Compression with Channel-wise Decoder

  • Indra Imanuel;Suk-Ho Lee
    • International Journal of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.74-83
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    • 2023
  • In this paper, we propose an image compression scheme which uses a demosaicking network and a channel-wise decoder in the decoding network. For the demosaicing network, we use as the input a colored mosaiced pattern rather than the well-known Bayer pattern. The use of a colored mosaiced pattern results in the mosaiced image containing a greater amount of information pertaining to the original image. Therefore, it contributes to result in a better color reconstruction. The channel-wise decoder is composed of multiple decoders where each decoder is responsible for each channel in the color image, i.e., the R, G, and B channels. The encoder and decoder are both implemented by wavelet based auto-encoders for better performance. Experimental results verify that the separated channel-wise decoders and the colored mosaic pattern produce a better reconstructed color image than a single decoder. When combining the colored CFA with the multi-decoder, the PSNR metric exhibits an increase of over 2dB for three-times compression and approximately 0.6dB for twelve-times compression compared to the Bayer CFA with a single decoder. Therefore, the compression rate is also increased with the proposed method than with the method using a single decoder on the Bayer patterned mosaic image.

Color Interpolation Algorithm for Pixel Resolution Modus of Image Sensor (영상센서의 출력 해상도 모드를 고려한 색상 보간 알고리즘)

  • Kim, Bu-Gong;Kim, Moon-Cheol
    • 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.