Neighbourhood image filters

Prerequisites

Before starting this lesson, you should be familiar with:

• Image pixels

Learning Objectives

After completing this lesson, learners should be able to:

• Understand the basic principle of a neighbourhood filter

Motivation

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

Concept

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

Activity

Use mean filter to facilitate image binarization

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 ()

KNIME

Formative assessment

Follow-up material

We recommend reading these modules next:

• Convolution filters

• Rank filters

Learn more: