Efficient edge detection by scale adaptation and recursive half-space filtering

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Abstract
A new edge detection algorithm has been developed and implemented that has both good speed and accuracy properties. The accuracy of the approach is derived from scale adaptation through anisotropic diffusion. The speed of the filter is based on recursive filtering. Specifically, the algorithm is implemented through a decomposition of the recursive filter into a convolution of two independent half space filters. This further improves the speed of the recursive filter and facilitates scale adaptation. The resulting algorithm is 1 - 2 orders of magnitude faster than comparable Gaussian based frequency domain and spatial domain methods. The new filter is omni-directional and super-elongated. It is also contour following, has computational complexity which is independent of scale, and has no truncation noise. The algorithm has been implemented and successfully applied to SPOT XS and Landsat MSS and TM imagery as one component of a region based image segmentation scheme.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

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