10 February 2006 Demosaicing: heterogeneity-projection hard-decision adaptive interpolation using spectral-spatial correlation
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A novel heterogeneity-projection hard-decision adaptive interpolation (HPHD-AI) algorithm is proposed in this paper for color reproduction from Bayer mosaic images. The proposed algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which the decision is made before interpolation. To do so, a new heterogeneity-projection scheme based on spectral-spatial correlation is proposed to decide the best interpolation direction from the original mosaic image directly. Exploiting the proposed heterogeneity-projection scheme, a hard-decision rule can be designed easily to perform the interpolation. We have compared this technique with three recently proposed demosaicing techniques: Lu's, Gunturk's and Li's methods, by utilizing twenty-five natural images from Kodak PhotoCD. The experimental results show that HPHD-AI outperforms all of them in both PSNR values and S-CIELab ▵Ε*ab measures.
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Chi-Yi Tsai, Kai-Tai Song, "Demosaicing: heterogeneity-projection hard-decision adaptive interpolation using spectral-spatial correlation", Proc. SPIE 6069, Digital Photography II, 606906 (10 February 2006); doi: 10.1117/12.639890; https://doi.org/10.1117/12.639890

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