Daniel Khashabi
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List of online demosaicing codes and binaries

Here I have gathered a list of available demosaicing codes or binaries files, which might be helpful for future works. Some of the algorithms have several implementations; so I am including all of them. If you have new online code for demosaicing or I have missed your code please let me know!

  1. AHD: Adaptive Homogeneity-directed Demosaicing

    1. Paper: Hirakawa, Keigo, and Thomas W. Parks. “Adaptive homogeneity-directed demosaicing algorithm.” Image Processing, IEEE Transactions on 14.3 (2005): 360-369.

    2. MATLAB

    3. Ubuntu: with –interpolation=ahd option.

  2. BI: Bilinear Interpolation

    1. Paper:

    2. MATLAB: Besides the code for “OS-AP”.

    3. C++: Besides the code for “CS”.

    4. Ubuntu: with –interpolation=bilinear option.

  3. CS: Contour Stencils

    1. Paper: Getreuer, Pascal. “Color demosaicing with contour stencils.” Digital Signal Processing (DSP), 2011 17th International Conference on. IEEE, 2011.

    2. C++

  4. Drectional-LMMSE: directional linear minimum mean square-error estimation

    1. Reference: Zhang, Lei, and Xiaolin Wu. “Color demosaicking via directional linear minimum mean square-error estimation.” Image Processing, IEEE Transactions on 14.12 (2005): 2167-2178.

    2. MATLAB: Included inside the code for “PCA-based Spatially Adaptive Denoising …”; or see this file

    3. C++

  5. HA: known as “Hamilton-Adams”

    1. Paper: Hamilton Jr, John F., and James E. Adams Jr. “Adaptive color plan interpolation in single sensor color electronic camera.” U.S. Patent No. 5,629,734. 13 May 1997.

    2. MATLAB: Besides the code for LPA-ICI

    3. C++: Besides the code for “AP”

  6. LPA-ICI: Local Polynomial Approximation

    1. Paper: Paliy, Dmitriy, et al. “Spatially adaptive color filter array interpolation for noiseless and noisy data.” International Journal of Imaging Systems and Technology 17.3 (2007): 105-122.

    2. MATLAB

  7. NAT: Non-local Adaptive Thresholding

    1. Paper: Zhang, Lei, et al. “Color demosaicking by local directional interpolation and nonlocal adaptive thresholding.” Journal of Electronic Imaging 20.2 (2011): 023016-023016.

    2. MATLAB

  8. NLM: Non-local Means

    1. Paper: ?

    2. MATLAB: Besides the code for “NAT(Non-local Adaptive Thresholding)”

  9. AP: Alternating Projections

    1. Paper: Gunturk, Bahadir K., Yucel Altunbasak, and Russell M. Mersereau. “Color plane interpolation using alternating projections.” Image Processing, IEEE Transactions on 11.9 (2002): 997-1013.

    2. MATLAB: Besides the code for “OS-AP”.

    3. MATLAB

    4. C++

  10. OS-AP: One Step AP(Alternating Projections)

    1. Paper: Lu, Yue M., Mina Karzand, and Martin Vetterli. “Demosaicking by alternating projections: theory and fast one-step implementation.” Image Processing, IEEE Transactions on 19.8 (2010): 2085-2098.

    2. MATLAB

  11. PCSD: Primary-Consistent Soft-Decision

    1. Binary

  12. PDF: Posterior Directional filtering

    1. Paper: Menon, Daniele, Stefano Andriani, and Giancarlo Calvagno. “Demosaicing With Directional Filtering and a posteriori Decision.” Image Processing, IEEE Transactions on 16.1 (2007): 132-141.

    2. MATLAB

  13. SA: SuccessiveApproximations

    1. MATLAB

  14. WECD: WeightedEdgeandColorsDifference

    1. Paper: Su, Chung-Yen. “Highly effective iterative demosaicing using weighted-edge and color-difference interpolations.” Consumer Electronics, IEEE Transactions on 52.2 (2006): 639-645.

    2. MATLAB

  15. ILI: Improved Linear Interpolation

    1. Paper: Malvar, Henrique S., Li-wei He, and Ross Cutler. “High-quality linear interpolation for demosaicing of Bayer-patterned color images.” Acoustics, Speech, and Signal Processing, 2004. Proceedings.(ICASSP’04). IEEE International Conference on. Vol. 3. IEEE, 2004.

    2. See the demosaic() function in MATLAB. To get more info run edit demosaic!

    3. C++

  16. LSLCD: Least Square Luma-Chroma Demoltiplexing

    1. Paper: Dubois, E., and G. Jeon. “Demosaicking of Noisy Bayer-Sampled Color Images with Least-Squares Luma-Chroma Demultiplexing and Noise Level Estimation.” (2011): 1-1.

    2. MATLAB

  17. LSSC: Leaning simultaneous sparsity coding

    1. Paper: Mairal, Julien, et al. “Non-local sparse models for image restoration.” Computer Vision, 2009 IEEE 12th International Conference on. IEEE, 2009.

    2. MATLAB

  18. SSDD: Self-similarity Driven Demosaicking

    1. Paper: Buades, Antoni, et al. “Self-similarity driven color demosaicking.” Image Processing, IEEE Transactions on 18.6 (2009): 1192-1202.

    2. C++