Automating the design of image processing pipelines for novel color filter arrays: local, linear, learned (L3) method

Qiyuan Tian; Steven Lansel; Joyce E. Farrell; Brian A. Wandell

doi:10.1117/12.2042565

7 March 2014 Automating the design of image processing pipelines for novel color filter arrays: local, linear, learned (L³) method

Qiyuan Tian, Steven Lansel, Joyce E. Farrell, Brian A. Wandell

Author Affiliations +

Proceedings Volume 9023, Digital Photography X; 90230K (2014) https://doi.org/10.1117/12.2042565
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

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 L³) for automatically creating an image processing pipeline. In this paper we describe the L³ algorithm and illustrate how we created a pipeline for a CFA organized as a 2×2 RGB/Wblock containing a clear (W) pixel. Under low light conditions, the L³ pipeline developed for the RGB/W CFA produces images that are superior to those from a matched Bayer RGB sensor. We also use L³ to learn pipelines for other RGB/W CFAs with different spatial layouts. The L³ algorithm shortens the development time for producing a high quality image pipeline for novel CFA designs.

Citation Download Citation

Qiyuan Tian, Steven Lansel, Joyce E. Farrell, and Brian A. Wandell "Automating the design of image processing pipelines for novel color filter arrays: local, linear, learned (L³) method", Proc. SPIE 9023, Digital Photography X, 90230K (7 March 2014); https://doi.org/10.1117/12.2042565

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