The Image Curvature Microscope: Accurate Curvature Computation at Subpixel Resolution
Adina Ciomaga, Pascal Monasse, Jean-Michel Morel
→ BibTeX
@article{ipol.2017.212,
    title   = {{The Image Curvature Microscope: Accurate Curvature Computation at Subpixel Resolution}},
    author  = {Ciomaga, Adina and Monasse, Pascal and Morel, Jean-Michel},
    journal = {{Image Processing On Line}},
    volume  = {7},
    pages   = {197--217},
    year    = {2017},
    doi     = {10.5201/ipol.2017.212},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2017.212}}
published
2017-07-28
reference
Adina Ciomaga, Pascal Monasse, and Jean-Michel Morel, The Image Curvature Microscope: Accurate Curvature Computation at Subpixel Resolution, Image Processing On Line, 7 (2017), pp. 197–217. https://doi.org/10.5201/ipol.2017.212

Communicated by Luis Álvarez
Demo edited by Pascal Monasse

Abstract

We detail in this paper the numerical implementation of the so-called image curvature microscope, an algorithm that computes accurate image curvatures at subpixel resolution, and yields a curvature map conforming with our visual perception. In contrast to standard methods, which would compute the curvature by a finite difference scheme, the curvatures are evaluated directly on the level lines of the bilinearly interpolated image, after their independent smoothing, a step necessary to remove pixelization artifacts. The smoothing step consists in the affine erosion of the level lines through a geometric scheme, and can be applied in parallel to all level lines. The online algorithm allows the user to visualize the image of curvatures at different resolutions, as well as the set of level lines before and after smoothing.

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