Fuzzy entropy thresholding and multi-scale morphological approach for microscopic image enhancement

Jiancan Zhou, Yuexiang Li, Linlin Shen

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Microscopic images provide lots of useful information for modern diagnosis and biological research. However, due to the unstable lighting condition during image capturing, two main problems, i.e., high-level noises and low image contrast, occurred in the generated cell images. In this paper, a simple but efficient enhancement framework is proposed to address the problems. The framework removes image noises using a hybrid method based on wavelet transform and fuzzy-entropy, and enhances the image contrast with an adaptive morphological approach. Experiments on real cell dataset were made to assess the performance of proposed framework. The experimental results demonstrate that our proposed enhancement framework increases the cell tracking accuracy to an average of 74.49%, which outperforms the benchmark algorithm, i.e., 46.18%.

Original languageEnglish
Title of host publicationNinth International Conference on Digital Image Processing, ICDIP 2017
EditorsXudong Jiang, Charles M. Falco
PublisherSPIE
ISBN (Electronic)9781510613041
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event9th International Conference on Digital Image Processing, ICDIP 2017 - Hong Kong, China
Duration: 19 May 201722 May 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10420
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference9th International Conference on Digital Image Processing, ICDIP 2017
Country/TerritoryChina
CityHong Kong
Period19/05/1722/05/17

Keywords

  • contrast enhancement
  • fuzzy entropy
  • Microscopic images
  • noise removal

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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