• Title/Summary/Keyword: Spatial Domain Demosaicing

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Demosaicing Algorithm by Gradient Edge Detection Filtering on Color Component (컬러 성분 에지 기울기 검출 필터링을 이용한 디모자이킹 알고리즘)

  • Jeon, Gwan-Ggil;Jung, Tae-Young;Kim, Dong-Hyung;Kim, Seung-Jong;Jeong, Je-Chang
    • 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.

Regularization-based Superresolution Demosaicing using Aperture Mask Wheels (조리개 마스크 휠을 이용한 정칙화 기반 초해상도 디모자이킹)

  • Shin, Jeongho
    • Journal of Broadcast Engineering
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    • v.23 no.1
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    • pp.146-153
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    • 2018
  • This paper presents a superresolution demosaicing technique that can restore high-resolution color image from differently blurred low resolution images in Bayer domain. The proposed superresolution demosaicing algorithm uses an aperture mask wheel to get differently blurred low resolution images, so we just need to estimate point spread function at each frame. In addition, it does not require image registration because there is no translational motion between low resolution images. By using a rotatable aperture mask wheel, consecutive captured images provide sufficiently exclusive information for superresolution. Therefore, the proposed method can reduce the registration error between the low-resolution image as well as the calculation amount for superresolution restoration. The existing lens system of the camera can be extended to obtain a superresolution image by only adding an rotatable aperture mask wheels. Finally, in order to verify the performance of the proposed system, experimental results are performed. The proposed method showed the significant improvements in the sense of spatial and color resolution.