Smoothed differentiation filters for images
- 4 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. ii, 121-126
- https://doi.org/10.1109/icpr.1990.119341
Abstract
A systematic approach to least square approximation of images and of their derivatives is presented. Derivatives of any order can be obtained by convolving the image with a priori known filters. It is shown that if orthonormal polynomial bases are employed the filters have closed-form solutions. The same filter is obtained when the fitted polynomial functions have one consecutive degree. Moment-preserving properties, sparse structure for some of the filters, and the relationship to the Marr-Hildreth and Canny edge detectors are proven.Keywords
This publication has 15 references indexed in Scilit:
- Toward a surface primal sketchPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Image Smoothing and Differentiation with Minimal-Curvature FiltersPublished by Defense Technical Information Center (DTIC) ,1989
- Optimal filters for the detection of linear patterns in 2-D and higher dimensional imagesPattern Recognition, 1987
- A Computational Approach to Edge DetectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1986
- On digital smoothing filters: A brief review of closed form solutions and two new filter approachesCircuits, Systems, and Signal Processing, 1986
- A Gaussian-weighted multiresolution edge detectorComputer Vision, Graphics, and Image Processing, 1985
- Theory of edge detectionProceedings of the Royal Society of London. B. Biological Sciences, 1980
- Picture Description Using Legendre PolynomialsComputer Graphics and Image Processing, 1975
- Smoothing and Differentiation of Data by Simplified Least Squares Procedures.Analytical Chemistry, 1964
- Curve Approximation by Means of Functions Analogous to the Hermite PolynomialsThe Annals of Mathematical Statistics, 1932