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Improved Weighted Non-Local Mean Filtering Algorithm for Laser Image Speckle Suppression.

Jin Cheng1, Yibo Xie1, Shun Zhou1

  • 1School of Optoelectronic Engineering, Xi'an Technological University, Xi'an 710000, China.

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|January 21, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an improved weighted non-local mean (IW-NLM) filter to reduce laser speckle noise in images. The method enhances image quality and detail preservation, offering better data for analysis.

Keywords:
denoisingimage processingnon-local mean filterspeckle noisestructured light

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Area of Science:

  • Optics and Photonics
  • Image Processing
  • Computer Vision

Background:

  • Laser speckle noise significantly degrades image quality due to laser coherence.
  • Effective noise reduction is crucial for accurate laser image analysis and subsequent processing.

Purpose of the Study:

  • To suppress laser speckle noise in laser images.
  • To enhance image detail preservation and pixel jump smoothing.
  • To provide improved data support for image processing analysis.

Main Methods:

  • Utilized a laser-structured light module and infrared camera for image acquisition.
  • Proposed an improved weighted non-local mean (IW-NLM) filtering method.
  • Implemented an SSI-based adaptive h-solving method for optimal parameter selection.

Main Results:

  • The IW-NLM filter effectively denoises laser images while preserving details.
  • Equivalent Number of Looks (ENL) improved by 0.80%.
  • Speckle Suppression Index (SSI) decreased from 4.69% to 2.55%.

Conclusions:

  • The proposed IW-NLM filtering method significantly suppresses laser speckle noise.
  • This method offers superior performance compared to standard non-local mean filtering.
  • The technique provides more accurate data for downstream image analysis applications.