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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.