Color demosaicking with an image formation model and adaptive PCA

  • Authors:

  • Dahua Gao;Xiaolin Wu;Guangming Shi;Lei Zhang

  • Affiliations:

  • School of Electronic Engineering, Xidian University, Xi'an, China and School of Science, Air Force Engineering University, Xi'an, China;School of Electronic Engineering, Xidian University, Xi'an, China and Department of Electrical & Computer Engineering, McMaster University, Hamilton, Canada;School of Electronic Engineering, Xidian University, Xi'an, China;Department of Computing, Hong Kong Polytechnic University, Hong Kong, China

  • Venue:
  • Journal of Visual Communication and Image Representation
  • Year:
  • 2012

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Abstract

Color demosaicking is an ill-posed inverse problem of image restoration. The performance of a color demosaicking algorithm depends on how thoroughly it can exploit domain knowledge to confine the solution space for the underlying true color image. We propose an @?"1 minimization technique for color demosaicking that exploits spectral and spatial sparse representations of natural images jointly. The spectral sparse representation is derived from a physical image formation model; the spatial sparse representation is based on a windowed adaptive principal component analysis. In some of most challenging cases of color demosaicking, the new technique outperforms many existing techniques by a large margin in PSNR and achieves higher visual quality.