Skip to content

Image co-localization


Feature list methods → Feature grouping → Image co-localization.

This module systematically identifies and groups images sharing similar spatial ion distributions. The user can choose between various similarity measure (e.g. pearson correlation) and can apply different filtering options before image comparison. image_colocalization



Feature Lists

Select feature list

Intensity threshold for co-localization

This intensity threshold is used to filter data points (pixel) before image co-localization.

Minimum number of co-located pixels

Minimum number of locations (pixels) that must be co-located.

Median filter window

Optional: Smooth over pixels to reduce noise and remove outliers, 3 ist recommended.

Ignore intensities below percentile

Optional: Only consider intensities above the selected percentile, 0.5 is recommended.

Ignore very high intensity outliers

Optional: Only consider values below the selected percentile, 0.99 is recommended.


Using the optional parameters Median filter window, Ignore intesities below percentile, and Ignore very high intensity outliers may result in better co-localization results.

Similarity measure

Select similarity measure.

Minimum similarity

"Minimum percentage for image similarity to be considered co-located."

Suffix (or auto)

Suffix to be added to the feature list name.


Last update: January 11, 2024 08:37:02