In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array—a physical construction whereby only a single color value is measured at each pixel location. We consider here the problem of color filter array design and its implications for spatial reconstruction quality. We pose this problem formally as one of simultaneously maximizing the spectral radii of luminance and chrominance channels subject to perfect reconstruction, and—after proving sub-optimality of a wide class of existing array patterns—provide a constructive method for its solution that yields robust, new panchromatic designs implementable as subtractive colors. Empirical evaluations on multiple color image test sets support our theoretical results, and indicate the potential of these patterns to increase spatial resolution for fixed sensor size, and to contribute to improved reconstruction fidelity as well as significantly reduced hardware complexity.

Source Code



K. Hirakawa, P.J. Wolfe, “Optimal Color Filter Array Design by Spatio-Spectral Sampling,” IEEE Trans. Image Processing, October 2008.[bibtex][pdf]

K. Hirakawa, P.J. Wolfe, “Spatio-Spectral Sampling and Color Filter Array Design,” in Single-Sensor Imaging: Methods and Applications for Digital Cameras, ed. R. Lukac, CRC Press, 2008. [bibtex][pdf]

K. Hirakawa, P.J. Wolfe, “Second Generation CFA and Demosaicking Design,” SPIE EI/VCIP, 2008. [bibtex][pdf]

K. Hirakawa, P.J. Wolfe, “Spatio-Spectral Color Filter Array for Enhanced Image Fidelity,” IEEE ICIP, 2007. [bibtex][pdf][award]

K. Hirakawa, P.J. Wolfe, “Fourier Domain Display Color Filter Array Design for Enhanced Image Fidelity,” IEEE ICIP, 2007. [bibtex][pdf]

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