Color filter array interpolation based on spatial adaptivity

Dmitriy Paliy; Radu Bilcu; Vladimir Katkovnik; Markku Vahviläinen

doi:10.1117/12.713354

27 February 2007 Color filter array interpolation based on spatial adaptivity

Dmitriy Paliy, Radu Bilcu, Vladimir Katkovnik, Markku Vahviläinen

Proceedings Volume 6497, Image Processing: Algorithms and Systems V; 649707 (2007) https://doi.org/10.1117/12.713354
Event: Electronic Imaging 2007, 2007, San Jose, CA, United States

Abstract

Conventional approach in single-chip digital cameras is a use of color filter arrays (CFA) in order to sample different spectral components. Demosaicing algorithms interpolate these data to complete red, green, and blue values for each image pixel, in order to produce an RGB image. In this paper we propose a novel demosaicing algorithm for the Bayer CFA. It is assumed that the initial estimates of color channels contain two additive components: the true values of color intensities and the errors. The errors are considered as an additive noise, and often called as a demosaicing noise, that has been removed. However, this noise is not white and strongly depends on a signal. Usually, the intensity of this noise is higher near edges of image details. We use spatially designed signal-adaptive filter to remove the noise. This filter is based on the local polynomial approximation (LPA) and the paradigm of the intersection of confidence intervals (ICI) applied for selection adaptively varying scales (window sizes) of LPA. The LPA-ICI technique is nonlinear and spatially-adaptive with respect to the smoothness and irregularities of the image. The efficiency of the proposed approach is demonstrated by simulation results.

Citation Download Citation

Dmitriy Paliy, Radu Bilcu, Vladimir Katkovnik, and Markku Vahviläinen "Color filter array interpolation based on spatial adaptivity", Proc. SPIE 6497, Image Processing: Algorithms and Systems V, 649707 (27 February 2007); https://doi.org/10.1117/12.713354

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available