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Neighbourhood image filters


Before starting this lesson, you should be familiar with:

Learning Objectives

After completing this lesson, learners should be able to:
  • Understand the basic principle of a neighbourhood filter


This module explains how image features (objects) can be enhanced using filters


graph TB P(pixel) --> |has| NBH(neighbourhood pixels) NBH --> |are used in| A(mathematical formula) A --> |compute new| NP(pixel value)


Use mean filter to facilitate image binarization

Show activity for:

ImageJ GUI

  • [ Open… ] “/image-analysis-training-resources/image_data/xy_8bit__nuclei_noisy_different_intensity.tif”
  • Appreciate that you cannot readily apply a threshold to binarize the image into two nuclei and background
  • Apply a mean filter [ Mean]
  • Try different neighbourhood sizes for mean filter
  • Appreciate that the filtered pixel values are slightly wrong due to integer data type
  • Binarize the filtered image by applying a threshold ()


Image binarization

Formative assessment

Follow-up material

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