Micromachines (Dec 2022)

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

  • Jin Cheng,
  • Yibo Xie,
  • Shun Zhou,
  • Anjiang Lu,
  • Xishun Peng,
  • Weiguo Liu

DOI
https://doi.org/10.3390/mi14010098
Journal volume & issue
Vol. 14, no. 1
p. 98

Abstract

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Laser speckle noise caused by coherence between lasers greatly influences the produced image. In order to suppress the effect of laser speckles on images, in this paper we set up a combination of a laser-structured light module and an infrared camera to acquire laser images, and propose an improved weighted non-local mean (IW-NLM) filtering method that adopts an SSI-based adaptive h-solving method to select the optimal h in the weight function. The analysis shows that the algorithm not only denoises the laser image but also smooths pixel jumps in the image, while preserving the image details. The experimental results show that compared with the original laser image, the equivalent number of looks (ENL) index of the IW-NLM filtered image improved by 0.80%. The speckle suppression index (SSI) of local images dropped from 4.69 to 2.55%. Compared with non-local mean filtering algorithms, the algorithm proposed in this paper is an improvement and provides more accurate data support for subsequent image processing analysis.

Keywords