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Bilateral edge filter: photometrically weighted, discontinuity based edge detection.

Radosav S Pantelic¹, Geoffery Ericksson, Nicholas Hamilton

¹Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld 4072, Australia.

Journal of Structural Biology

|September 8, 2007

Summary

A new Bilateral edge filter enhances edge detection in microscopy by minimizing noise and artifacts. This method offers improved selectivity and speed compared to traditional filters, proving effective for single particle and tomographic analysis.

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Area of Science:

Image processing
Microscopy
Computational biology

Background:

Traditional linear filters struggle with noise and artifacts in image analysis.
Edge detection is crucial for single particle analysis and 3D volume segmentation in microscopy.
Existing edge detectors like LoG and Marr-Hildreth have limitations in selectivity and noise handling.

Purpose of the Study:

To introduce and evaluate a novel Bilateral edge filter for enhanced edge detection.
To compare the performance of the Bilateral edge filter against traditional and leading edge detection methods.
To highlight the filter's advantages in noise reduction, artifact minimization, and efficiency for microscopy applications.

Main Methods:

Adaptation of the Bilateral filter using photometric weighting for discontinuity identification.

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Comparative analysis against Logarithmic Gabor (LoG), Marr-Hildreth, and Canny edge detectors.

Evaluation of performance in single particle analysis and tomographic segmentation tasks.

Main Results:

The Bilateral edge filter significantly outperforms LoG and Marr-Hildreth detectors.
Results are comparable in quality to the Canny edge-detector.
The Bilateral edge filter demonstrates superior noise and artifact reduction.
It requires only a single parameter adjustment, unlike the Canny edge-detector.

Conclusions:

The Bilateral edge filter is a robust and efficient tool for edge detection in microscopy.
Its advantages include speed, simplicity, and effective noise/artifact suppression.
The filter shows great promise for applications in single particle analysis and tomography.