Heterogeneity-projection hard-decision color interpolation using spectral-spatial correlation

Abstract

This paper presents a novel heterogeneity-projection hard-decision (HPHD) color interpolation procedure for reproduction of Bayer mosaic images. The proposed algorithm aims to estimate the optimal interpolation direction and perform hard-decision interpolation, in which each pixel only needs to be interpolated once. A new heterogeneity-projection scheme based on a novel spectral-spatial correlation concept is proposed to estimate the best interpolation direction directly from the original mosaic image. Using the proposed heterogeneity-projection scheme, a hard-decision rule can be decided before performing the interpolation. The advantage of this scheme is that it provides an efficient way for decision-based algorithms to generate improved results using fewer computations. Compared with three recently reported demosaicing techniques, Gunturk's, Lu's, and Li's methods, the proposed HPHD outperforms all of them in both PSNR values and S-CIELAB Delta E-ab* measures by utilizing 25 natural images from Kodak PhotoCD.