4.6 Article

HAUSDORFF DERIVATIVE LAPLACIAN OPERATOR FOR IMAGE SHARPENING

Publisher

WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0218348X19500609

Keywords

Image Sharpening; Hausdorff Fractal Distance; Hausdorff Derivative; Laplacian Operator

Funding

  1. National Natural Science Foundation of China [11802151, 11572111, 11372097]
  2. 111 Project [B12032]
  3. Key Research and Development Plan of Shandong Province [2018GGX105004]

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Image sharpening based on the partial differential equations plays an important role in the fields of image processing. It is an effective technique to clear and sharpen image features, and provides a higher resolution for the subsequent processing. This paper makes the first attempt to employ the Hausdorff derivative Laplacian operator to sharpen the images. In terms of the visual quality of details, contours and edges, the original images and noisy images were sharpened by using an appropriate Hausdorff derivative order. Numerical results indicate that the Hausdorff derivative Laplacian operator outperforms the high-pass filtering, the Roberts operator and the traditional integer-order Laplacian operator. In comparison with the existing methods for the image sharpening, the proposed new methodology could be considered as a competitive alternative.

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