Scale-space and edge detection using anisotropic diffusion

1990/07/01 by Pietro Perona, Jitendra Malik · 10 citations
Computer Science · Mathematics · #Algorithm #Anisotropic diffusion #Artificial intelligence #Boundary (topology) #Class (philosophy) #Computer science #Computer vision #Diffusion #Edge detection #Enhanced Data Rates for GSM Evolution #Image (mathematics) #Image Retrieval and Classification Techniques #Image and Signal Denoising Methods #Image processing #Mathematical analysis #Mathematics #Maxima and minima #Medical Image Segmentation Techniques #Physics #Scale (ratio) #Scale space #Smoothing #Space (punctuation)

paper · doi:10.1109/34.56205

openalex publication_date 1990/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06

Abstract

A new definition of scale-space is suggested, and a class of algorithms used to realize a diffusion process is introduced. The diffusion coefficient is chosen to vary spatially in such a way as to encourage intraregion smoothing rather than 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 the approach remain sharp, a high-quality edge detector which successfully exploits global information is obtained. Experimental results are shown on a number of images. Parallel hardware implementations are made feasible because the algorithm involves elementary, local operations replicated over the image.>

Citations

• The structure of images
• Optimal approximations by piecewise smooth functions and associated variational problems
• A Computational Approach to Edge Detection

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