A Demosaicking Algorithm with Adaptive Inter-Channel Correlation
Joan Duran, Antoni Buades
→ BibTeX
    title   = {{A Demosaicking Algorithm with Adaptive Inter-Channel Correlation}},
    author  = {Duran, Joan and Buades, Antoni},
    journal = {{Image Processing On Line}},
    volume  = {5},
    pages   = {311--327},
    year    = {2015},
    doi     = {10.5201/ipol.2015.145},
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2015.145}}
Joan Duran, and Antoni Buades, A Demosaicking Algorithm with Adaptive Inter-Channel Correlation, Image Processing On Line, 5 (2015), pp. 311–327. https://doi.org/10.5201/ipol.2015.145

Communicated by Pablo Musé
Demo edited by Jose-Luis Lisani


Most common cameras use a CCD sensor device measuring a single color per pixel. Demosaicking is the interpolation process by which one can infer a full color image from such a matrix of values, thus interpolating the two missing components per pixel. Most demosaicking methods take advantage of inter-channel correlation locally selecting the best interpolation direction. The obtained results look convincing except when local geometry cannot be inferred from neighboring pixels or channel correlation is low. In these cases, these algorithms create interpolation artifacts such as zipper effect or color aliasing. This paper discusses the implementation details of the algorithm proposed in [J. Duran, A. Buades, ``Self-Similarity and Spectral Correlation Adaptive Algorithm for Color Demosaicking'', IEEE Transactions on Image Processing, 23(9), pp. 4031--4040, 2014]. The proposed method involves nonlocal image self-similarity in order to reduce interpolation artifacts when local geometry is ambiguous. It further introduces a clear and intuitive manner of balancing how much channel-correlation must be taken advantage of.