Automating the design of image processing pipelines for novel color filter arrays: Local, Linear, Learned (L) method

نویسندگان

  • Qiyuan Tian
  • Steven Lansel
  • Joyce E. Farrell
  • Brian A. Wandell
چکیده

The high density of pixels in modern color sensors provides an opportunity to experiment with new color filter array (CFA) designs. A significant bottleneck in evaluating new designs is the need to create demosaicking, denoising and color transform algorithms tuned for the CFA. To address this issue, we developed a method(local, linear, learned or L) for automatically creating an image processing pipeline. In this paper we describe the L algorithm and illustrate how we created a pipeline for a CFA organized as a 2×2 RGB/W block containing a clear (W) pixel. Under low light conditions, the L pipeline developed for the RGB/W CFA produces images that are superior to those from a matched Bayer RGB sensor. We also use L to learn pipelines for other RGB/W CFAs with different spatial layouts. The L algorithm shortens the development time for producing a high quality image pipeline for novel CFA designs.

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تاریخ انتشار 2014