A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Uniqueness of the Gaussian Kernel for Scale-Space Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Synthesis of Gaussian Filters by Cascaded Uniform Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
A regularized solution to edge detection
Journal of Complexity
Multiresolution Feature Extraction and Selection for Texture Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital image processing
Regularization, Scale-Space, and Edge Detection Filters
Journal of Mathematical Imaging and Vision
Differentiation-Based Edge DetectionUsing the Logarithmic Image Processing Model
Journal of Mathematical Imaging and Vision
Graduated Nonconvexity by Functional Focusing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Errors in the estimation of gradient direction using IIR and FIR implementations
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Efficient computation for Whittaker-Henderson smoothing
Computational Statistics & Data Analysis
Discrete H∞ estimator design of unknown input: Game-theoretic approach
Signal Processing
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Least squares approximation problems that are regularized with specified highpass stabilizing kernels are discussed. For each problem, there is a family of discrete regularization filters (R-filters) which allow an efficient determination of the solutions. These operators are stable symmetric lowpass filters with an adjustable scale factor. Two decomposition theorems for the z-transform of such systems are presented. One facilitates the determination of their impulse response, while the other allows an efficient implementation through successive causal and anticausal recursive filtering. A case of special interest is the design of R-filters for the first- and second-order difference operators. These results are extended for two-dimensional signals and, for illustration purposes, are applied to the problem of edge detection. This leads to a very efficient implementation (8 multiplies+10 adds per pixel) of the optimal Canny edge detector based on the use of a separable second-order R-filter.