Scale-Space and Edge Detection Using Anisotropic Diffusion


Abstracf-The scale-space technique introduced by Witkin involves generating coarser resolution images by convolving the original image with a Gaussian kernel. This approach has a major drawback: it is difficult to obtain accurately the locations of the " semantically meaningful " edges at coarse scales. In this paper we suggest a new definition of scale-space, and introduce a class of algorithms that realize it using a diffusion process. The diffusion coefficient is chosen to vary spatially in such a way as to encourage intraregion smoothing in preference to interregion smoothing. It is shown that the " no new maxima should be generated at coarse scales " property of conventional scale space is preserved. As the region boundaries in our approach remain sharp, we obtain a high quality edge detector which successfully exploits global information. Experimental results are shown on a number of images. The algorithm involves elementary, local operations replicated over the image making parallel hardware implementations feasible.

DOI: 10.1109/34.56205

Extracted Key Phrases

Showing 1-10 of 18 references

His research interests are in computational and biological vision

  • 1990

Scale space and edge detection using anisotropic diffusion

  • P Perona, J Malik
  • 1987

Optimal approximation of piecewise smooth functions and associated variational problems

  • Massachusetts Lab, D Inst, J Mumford, Shah
  • 1985
Showing 1-10 of 4,230 extracted citations
Citations per Year

20,090 Citations

Semantic Scholar estimates that this publication has received between 18,690 and 21,567 citations based on the available data.

See our FAQ for additional information.