One-Dimensional Regularization with Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Estimation of Contour Properties by Cross-Validated Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Detection of Dominant Points on Digital Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiscanning Approach Based on Morphological Filtering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Spectrum and Multiscale Shape Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space for Discrete Signals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scaling Theorems for Zero-Crossings
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Contour Decomposition Using a Constant Curvature Criterion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Smoothing: A General Tool for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space From Nonlinear Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiscale Nonlinear Decomposition: The Sieve Decomposition Theorem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scaling Theorems for Zero Crossings of Bandlimited Signals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iterative Smoothed Residuals: A Low-Pass Filter for Smoothing With Controlled Shrinkage
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Reproducible Smoothing Without Shrinkage
IEEE Transactions on Pattern Analysis and Machine Intelligence
Partial Smoothing Splines for Noisy +Boundaries with Corners
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digitized Circular Arcs: Characterization and Parameter Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Extended Class of Scale-Invariant and Recursive Scale Space Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multiscale Method for the Reassembly of Two-Dimensional Fragmented Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Smoothing via Contextual and Local Discontinuities
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the convergence of planar curves under smoothing
IEEE Transactions on Image Processing
| Hi-index | 0.14 |
In several applications where binary contours are used to represent and classify patterns, smoothing must be performed to attenuate noise and quantization error. This is often implemented with local weighted averaging of contour point coordinates, because of the simplicity, low-cost and effectiveness of such methods. Invoking the "optimality" of the Gaussian filter, many authors will use Gaussian-derived weights. But generally these filters are not optimal, and there has been little theoretical investigation of local weighted averaging methods per se. This paper focuses on the direct derivation of optimal local weighted averaging methods tailored towards specific computational goals such as the accurate estimation of contour point positions, tangent slopes, or deviation angles. A new and simple digitization noise model is proposed to derive the best set of weights for different window sizes, for each computational task. Estimates of the fraction of the noise actually removed by these optimum weights are also obtained. Finally, the applicability of these findings for arbitrary curvature is verified, by numerically investigating equivalent problems for digital circles of various radii.