JOURNAL ARTICLE

On optimal infinite impulse response edge detection filters

Sudeep SarkarKim L. Boyer

Year: 1991 Journal:   IEEE Transactions on Pattern Analysis and Machine Intelligence Vol: 13 (11)Pages: 1154-1171   Publisher: IEEE Computer Society

Abstract

The authors outline the design of an optimal, computationally efficient, infinite impulse response edge detection filter. The optimal filter is computed based on Canny's high signal to noise ratio, good localization criteria, and a criterion on the spurious response of the filter to noise. An expression for the width of the filter, which is appropriate for infinite-length filters, is incorporated directly in the expression for spurious responses. The three criteria are maximized using the variational method and nonlinear constrained optimization. The optimal filter parameters are tabulated for various values of the filter performance criteria. A complete methodology for implementing the optimal filter using approximating recursive digital filtering is presented. The approximating recursive digital filter is separable into two linear filters, operating in two orthogonal directions. The implementation is very simple and computationally efficient. has a constant time of execution for different sizes of the operator, and is readily amenable to real-time hardware implementation.< >

Keywords:
Digital filter Filter (signal processing) Filter design Linear filter Spurious relationship Algorithm Finite impulse response Infinite impulse response Root-raised-cosine filter Mathematics Adaptive filter Computer science Impulse noise Impulse response Control theory (sociology) Mathematical optimization Artificial intelligence Computer vision Statistics

Metrics

137
Cited By
7.82
FWCI (Field Weighted Citation Impact)
46
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Structural Health Monitoring Techniques
Physical Sciences →  Engineering →  Civil and Structural Engineering
Image and Object Detection Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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