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Linear demosaicing inspired by the human visual system.

David Alleysson1, Sabine Süsstrunk, Jeanny Hérault

  • 1Laboratory for Psychology and NeuroCognition, University Pierre-Mendes France, 38040 Grenoble, France. david.alleysson@upmf-grenoble.fr

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|April 14, 2005
PubMed
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Single-chip cameras, like the human eye, capture limited color data per pixel. This study models this, enabling better demosaicing algorithms to improve image quality by reducing visual artifacts.

Area of Science:

  • Digital Image Processing
  • Computational Vision
  • Color Science

Background:

  • Single-chip color cameras capture one color band per spatial location, similar to the human visual system.
  • This limited spectral information per pixel presents challenges for reconstructing full-color images.

Purpose of the Study:

  • To develop a model characterizing single-color-per-position images as luminance and chrominance components.
  • To investigate the relationship between luminance and chrominance in the Fourier domain for demosaicing.
  • To propose solutions for visual artifacts arising from demosaicing.

Main Methods:

  • Defined a model representing single-color images as coded luminance and chrominance.
  • Analyzed the Fourier domain arrangement of luminance and chrominance.

Related Experiment Videos

  • Investigated aliasing artifacts and proposed preprocessing filters for demosaicing.

    • Main Results:

    • Luminance is captured with full spatial resolution, while chrominance is subsampled.
    • Demosaicing artifacts are identified as aliasing between luminance and chrominance.
    • A preprocessing filter approach effectively reduces visual artifacts.

    Conclusions:

    • The proposed model provides new insights into single-color image representation.
    • Formal procedures for designing effective demosaicing algorithms are enabled.
    • The approach demonstrates superior performance compared to existing methods.