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Related Concept Videos

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Related Experiment Video

Updated: Jun 19, 2026

Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

Single-image vignetting correction.

Yuanjie Zheng1, Stephen Lin, Chandra Kambhamettu

  • 1Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716-2712, USA. zhengyuanjie@gmail.com

IEEE Transactions on Pattern Analysis and Machine Intelligence
|October 17, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a robust method to determine image vignetting from a single photo, effectively using textured and untextured areas for accurate vignetting function estimation.

Related Experiment Videos

Last Updated: Jun 19, 2026

Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

Area of Science:

  • Computer Vision
  • Image Processing

Background:

  • Vignetting is a common optical distortion in images.
  • Accurate vignetting correction is crucial for image quality and analysis.
  • Existing methods often struggle with untextured regions or require multiple images.

Purpose of the Study:

  • To develop a robust method for estimating the vignetting function from a single image.
  • To effectively utilize both textured and untextured image regions for vignetting estimation.
  • To improve the accuracy and reliability of vignetting correction techniques.

Main Methods:

  • Adaptation of image segmentation techniques to identify reliable regions for vignetting estimation.
  • Leveraging frequency characteristics and physical properties of vignetting to differentiate it from other intensity variations.
  • Implementation of outlier pixel rejection to enhance the robustness of the estimation process.

Main Results:

  • Demonstrated effectiveness on a wide variety of images with simulated and natural vignetting.
  • Successful handling of both textured and untextured image areas.
  • Robust vignetting function determination from a single image.

Conclusions:

  • The proposed method offers a robust and effective solution for single-image vignetting estimation.
  • The technique maximizes information utilization by incorporating both textured and untextured regions.
  • Further analysis of failure cases provides insights for future improvements.