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---
title: Difference of Gaussian
layout: page
layout: module
prerequisites:
- TODO
objectives:
- TODO
motivation: >
TODO
concept_map: >
graph TD
IM("Image") --> SBl("Small blur")
IM --> LBl("Large blur")
SBl --> NF("Noise filtered")
SBl --> SBlLBl("Small blur - Large blur")
LBl --> SBlLBl
LBl --> LB("Local background")
SBlLBl -- gives --> DoG("Differece of Gaussians (DoG)")
DoG -- is related to --> LoG("Laplacian of Gaussian (LoG)")
# figure: /path/to/image.png
# figure_legend: TODO
activity_preface: |
- Open image: xy_8bit__two_spots_noisy_uneven_background.tif
- Appreciate that you cannot readily threshold the spots
- Compute DoG:
- Copy image and blur with a Gaussian of small sigma -> Gs
- Copy image and blur with a Gaussian of bigger sigma -> Gb
- For the official DoG: `rb = sqrt(2) * rs`
- Create `DoG = Gs - Gb`
- Appreciate that now it is possible to threshold the spots in the DoG image
activities:
# "TODO": /path/to/activity/file.md
exercises_preface: >
TODO
exercises:
# "TODO": /path/to/exercise/file.md
learn_next:
- TODO
external_links:
- "[Wikipedia: Difference of Gaussians](https://en.wikipedia.org/wiki/Difference_of_Gaussians)"
- "[FeatureJ: plugins for feature extraction from images](https://imagescience.org/meijering/software/featurej/)"
- "[CellProfiler module for enhancing/suppressing features in an image (Python)](https://github.com/CellProfiler/CellProfiler/blob/master/cellprofiler/modules/enhanceorsuppressfeatures.py#L4)"
---
## Difference of Gaussian (DoG)
<img src='https://g.gravizo.com/svg?
digraph G {
shift [fontcolor=white,color=white];
image -> "small blur";
image -> "large blur";
"small blur" -> "noise filtered";
"large blur" -> "local background";
"small blur" -> "small blur - large blur" -> "DoG";
"large blur" -> "small blur - large blur" -> "DoG";
"DoG" -> "Laplacian of Gaussian (LoG)" [label=" is related"];
}
'/>
### Activity: Enhance spots in noisy image with uneven background
- Open image: xy_8bit__two_spots_noisy_uneven_background.tif
- Appreciate that you cannot readily threshold the spots
- Compute DoG:
- Copy image and blur with a Gaussian of small sigma -> Gs
- Copy image and blur with a Gaussian of bigger sigma -> Gb
- For the official DoG: `rb = sqrt(2) * rs`
- Create `DoG = Gs - Gb`
- Appreciate that now it is possible to threshold the spots in the DoG image
### Learn more
- https://imagescience.org/meijering/software/featurej/
- https://en.wikipedia.org/wiki/Difference_of_Gaussians
- https://github.com/CellProfiler/CellProfiler/blob/master/cellprofiler/modules/enhanceorsuppressfeatures.py#L4