Automatic image colorization based on SVD and lab color space

  • Authors

    • Nidhal K. El .Abbadi University of Kufa
    • Eman Saleem university of Kufa
    2019-07-14
    https://doi.org/10.14419/ijet.v7i4.26186
  • Colorization, Gray Image, Image Processing, Lab Color Space, SVD.

  • Abstract

    Images colorization is the operation of append colors to the grayscale image by using a reference color image. The main problem of  coloring a grayscale image involves constructing three dimensional image from one dimensional array. The current paper developed a fully automatic image colorization system based on the singular value decomposition (SVD) transformation. SVD used to measuring the best pixel in the reference image proper to colorize the gray image, depending on comparing the pixel value and their neighbor values of the gray image with pixel value and their neighbors in the reference image. Using the color space is more suitable to many digital image processing than the RGB, for that the author suggested to convert reference image to the CIELab color space in this proposal. Gray   image normalized according to the (L channel) of reference image. Ultimately, the intensity of the selected pixel in the gray image   combine with (a, b channels) values of the best pixel from CIELab color space of reference image, which is finally converted to RGB color image. The suggested algorithm is the first algorithm utilized the SVD for image colorization which give good and promised results compared with other methods, and can be enhanced in the future.

     

     

  • References

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  • How to Cite

    K. El .Abbadi, N., & Saleem, E. (2019). Automatic image colorization based on SVD and lab color space. International Journal of Engineering & Technology, 8(2), 63-71. https://doi.org/10.14419/ijet.v7i4.26186

    Received date: 2019-01-19

    Accepted date: 2019-06-09

    Published date: 2019-07-14