Image Acquisition – Optimal Color Filter Array(CFA)

Digital color cameras acquire color images by means of a sensor on which a color filter array (CFA) is overlaid. The Bayer CFA dominates the consumer market, but there has recently been a renewed interest for the design of CFAs [2]–[6]. However, robustness to noise is often neglected in the design, though it is crucial in practice. In this paper, we present a new 2 x 3-periodic CFA which provides, by construction, the optimal tradeoff between robustness to aliasing, chrominance noise and luminance noise. Moreover, a simple and efficient linear demosaicking algorithm is described, which fully exploits the spectral properties of the CFA. Practical experiments confirm the superiority of our design, both in noiseless and noisy scenarios.

Existing System:

So far, emphasis in CFA design and demosaicking has been put on the minimization of the aliasing artifacts due to spectral overlap of the modulated color channels in the mosaicked image. But with the always increasing resolution of the sensors, aliasing has become a minor issue. In most cases, the optical system is the limiting factor, so that the scene which is sampled by the sensor is bandlimited and moiré artifacts never appear. On the other side, in high-end digital single-lens reflex cameras equipped with expensive and high-quality lenses, an anti-aliasing filter is overlaid on the sensor to get rid of aliasing issues, typically a layer of birefringent material. Still, robustness to aliasing is an important criterion in CFA design, not so much because of potential moiré artifacts, but because it determines the intrinsic resolution of the imaging system.

Proposed System:

We argue that robustness to noise is more important than robustness to aliasing. High sensitivity properties allow, when acquiring a given picture, to reduce the exposure time (for less blur due to camera shake), to increase the aperture (for increased depth-of-field, hence less out-of-focus blur), or to use a lower ISO setting and a less destructive denoising process. This is particularly important for photography in low light level environments. Hence, there is a real need for new CFAs with improved sensitivity, so that maximum energy of the color scene is packed into the mosaicked image.

Modules:

  • Load Image/Save Image
  • Image processing techniques
  • Color Filters
  • HSL Color Space
  • Binarization
  • Morphology
  • Convolution and Correlation
  • Edge Detectors
  • Histogram
  • Gamma Correction filter

Tools Used:

Front End : C#.NET