A new CFA interpolation framework

  • Authors:

  • Rastislav Lukac;Konstantinos N. Plataniotis;Dimitrios Hatzinakos;Marko Aleksic

  • Affiliations:

  • The Edward S. Rogers Sr. Department of ECE, University of Toronto, Toronto, Ont., Canada;The Edward S. Rogers Sr. Department of ECE, University of Toronto, Toronto, Ont., Canada;The Edward S. Rogers Sr. Department of ECE, University of Toronto, Toronto, Ont., Canada;The Edward S. Rogers Sr. Department of ECE, University of Toronto, Toronto, Ont., Canada

  • Venue:
  • Signal Processing
  • Year:
  • 2006

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Abstract

The paper introduces a new color filter array (CFA) interpolation method for digital still cameras. The proposed interpolation scheme is able to (i) overcome the hardware limitations of existing CFA based image acquisition solutions, and (ii) restore color images with excellent visual quality. The scheme employs an adaptive edge-sensing mechanism which operates along the vertical, horizontal and diagonal directions to Correctly interpolate unavailable color components. Building on the computed edge-sensing map and a refined color-difference model, a new correlation-correction algorithm is introduced. In addition to the basic model, adaptively determined correction operations are also discussed and analyzed. The solutions proposed here, described in a novel vector notation, constitute a unique CFA interpolation framework, which readily unifies previous, seemingly unrelated, results. Simulation studies indicate that the proposed method is computationally efficient and yields excellent performance, in terms of subjective and objective image quality measures, while outperforming state-of-the-art CFA interpolation methods.