Demosaicing enhancement using pixel-level fusion

Abstract

Bayer pattern has been widely used in commercial digital cameras. In NASA's mast camera (Mastcams) onboard the Mars rover Curiosity, Bayer pattern has also been used in capturing the RGB bands. It is well known that debayering, also known as demosaicing in the literature, introduces artifacts such as false colors and zipper edges. In this paper, we first present four fusion approaches, including weighted and the well-known alpha-trimmed mean filtering approaches. Each fusion approach combines demosaicing results from seven debayering algorithms in the literature, which are selected based on their performance mentioned in other survey papers and the availability of open source codes. Second, we present debayering results using two benchmark image data sets: IMAX and Kodak. It was observed that none of the seven algorithms in the literature can yield the best performance in terms of peak signal-to-noise ratio (PSNR), CIELAB score, and subjective evaluation. Although the fusion algorithms are simple, it turns out that the debayering performance can be improved quite dramatically after fusion based on our extensive evaluations. In particular, the average PSNR improvements of the weighted fusion algorithm over the best individual method are 1.1 dB for the IMAX database and 1.8 dB for the Kodak database, respectively. Third, we applied the various algorithms to 36 actual Mastcam images. Subjective evaluation indicates that the fusion algorithms still work well, but not as good as the existing debayering algorithm used by NASA.

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