Colour Algorithms for Monotonic Nonlinear CMOS Image Sensors

  • Author / Creator
    Hussain, Syed
  • Compared to human vision, dynamic range (DR) is a limiting factor for modern cameras. While conventional complementary metal-oxide-semiconductor (CMOS) image sensors are limited in their ability to capture DR, nonlinear
    CMOS image sensors, e.g., with logarithmic (log) or linear-logarithmic (linlog) responses, are able to capture high/wide DRs in single exposures at video rates. Considering the drawbacks of such sensors, this thesis proposes and validates
    new algorithms, for colour correction and demosaicking, that are specially designed for nonlinear sensors where the response is a monotonic function of stimulus, a property of log and linlog sensors. The proposed colour correction has a nonlinear part, which employs cubic Hermite splines, followed by a linear part. To estimate relevant parameters, calibration with a colour chart is required. The method is validated, through simulation, using a combination of experimental data, from a monochromatic log sensor, and spectral data, from
    the literature. The proposed nonlinear demosaicking uses weighted medians to filter pixels exhibiting salt-and-pepper noise (SPN), a drawback of nonlinear sensors, while determining a colour for each channel at every pixel. Variations of the method are considered and evaluated. To produce mosaicked images for testing, a Kodak true colour image set is subsampled, in a Bayer colour filter array pattern, and SPN of varying densities is added. Results of the proposed
    method are compared to those from a popular literature method. Finally, future directions of this work are discussed, such as a fi xed-point implementation of both algorithms and ways to facilitate additional experimental results.

  • Subjects / Keywords
  • Graduation date
    Spring 2020
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
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