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Updated: Oct 8, 2025

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

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Published on: March 13, 2017

Corrigendum: Identifying single electron charge sensor events using wavelet edge detection

J R Prance¹, B J Van Bael², C B Simmons²

¹Department of Physics, Lancaster University, Lancaster, LA1 4YB, United Kingdom.

|December 28, 2021

Summary

This summary is machine-generated.

Wavelet edge detection is superior to thresholding for image analysis with white and 1/f noise. New results confirm this finding after correcting simulated noise descriptions.

Keywords:

charge detection quantum information quantum point contacts semiconductor quantum dots wavelet transform

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Last Updated: Oct 8, 2025

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Published on: March 13, 2017

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Area of Science:

Signal Processing
Image Analysis
Computational Imaging

Context:

Benchmarking edge detection algorithms requires accurate noise simulation.
Previous work incorrectly described the simulated noise.
This study corrects the noise description and re-evaluates algorithm performance.

Purpose:

To correct the description of simulated noise used in benchmarking wavelet edge detection.
To provide new results based on accurately simulated noise.
To reaffirm the superiority of wavelet edge detection over thresholding.

Summary:

The simulated noise for benchmarking wavelet edge detection was corrected.
New results confirm that wavelet edge detection outperforms thresholding.
This holds true for both white noise and 1/f noise conditions.

Impact:

Provides accurate methodology for future research in image noise analysis.
Confirms the robustness and effectiveness of wavelet edge detection.
Offers improved image processing techniques for noisy datasets.