Image Intensity Processing

Revision as of 14:36, 18 December 2013 by Amacall (talk | contribs) (Pseudo-linescan)

Intensity vs Time analysis

Brightness and Contrast

Brightness contrast pic.png









Getting intensity values from single ROI




Dynamic intensity vs Time analysis


Getting intensity values from multiple ROIs


The Multi Measure plugin that comes with the installation is v3.2.



3. Rename this image something memorable.







Roi select all.jpg




Ratio Analysis

Intensity ratio analysis.jpg








 Ratio Analysis Using ROI manager

1.Subtract the background from the image.



4. Run the plugin.


To generate a reference image:


2. Adjust the brightness and contrast if necessary.




Obtaining timestamp data

Zeiss LSM




Noran movies can be opened in several ways: File>Import>Noran movie opens entire movie as an image stack. File>Import>Noran Selection… allows you to specify a range of frames to be opened as a stack. The Noran SGI plugins are not bundled with the Fiji package. To receive them, please contact or their author, Greg Joss, so he can keep track of users. Greg Joss is in the Dept. of Biology, Macquarie University, Sydney, Australia.







This example shows the elementary calcium events preceding a calcium wave. HeLa cell loaded with the calcium-sensitive fluorophore, Fluo-3 and imaged whilst responding to application of histamine. (A). Frame taken from time-course at the peak of the calcium-release response. (B) The line of pixels along X-Y was taken and stacked side by side from right-to left to generate a "pseudo-line scan". This allows visualisation of the progression of the wave from its initiation site.

 Fiji assumes stacks to be z-series rather than t-series so many functions related to the third-dimension of an image stack are called “z-” something – e.g. “z-axis profile” is intensity over time plot.

FRAP (Fluorescence Recovery After Photobleaching) Analysis

The FRAP profiler plugin will analyse the intensity of a bleached ROI over time and normalise this against the intensity of the whole cell. It will then find the minimum intensity in the bleached ROI and fit the recovery  from this point.

To use:

1. Open the ROI manager.

2. Draw around the bleached ROI and Add to the ROI manager.

3. Draw around the whole cell and add to ROI manager. The normalisation corrects for the bleaching dues to image acquisition and assumes the whole cell is in the field of view.

The plugin assumes the larger of the last two ROIs in the ROI manager is the whole cell ROI and the smaller the bleached ROI.

4. Run the FRAP profiler plugin.

5. The plugin will return the intensity vs time plot; the normalised intensity vs time plot of the bleached area and the curve fit.


normalised intensity at time t = It = (Ibt ÷ Ibmax)  ÷ (Ict ÷ Icmax)

Ibt= intensity of bleached ROI at time t.

Ict= intensity of whole cell at time t.

Non-linear contrast stretching


More control of the brightness and contrast adjustment can be achieved with the“Process/Enhance contrast” menu command. Here, when applied to a stack, it applies the adjustment based on each slice’s histogram, not just the one currently displayed as is done with the Brightness and Contrast window.

“Equalize contrast” applies a non-linear stretch of the histogram based on the square root of the intensity (see online guide to image processing:

Equalize histrogram.jpg


This can be though of as a non-linear histogram adjustment. Faint objects can be made more intense without saturating bright objects (gamma <1). Similarly, medium-intensity objects can be made fainter without dimming the bright objects (gamma > 1). The intensity of each pixel is “raised to the power” of the gamma value and then scaled to 8-bits or the min and max of 16-bit images.



Gamma pic.jpg


See the online reference: for a simple explanation of digital filtering.

Filters can be found under the menu item “Process/Filters.... Typically use a “Radius (pixels)” of 1 which equates to a 3×3 “kernel” – see online reference.

Mean filter: the pixel is replaced with the average of it and its neighbours within the radius. The menu item “Process/Smooth” is a 3×3 mean filter.

Gaussian filter: The is similar to smoothing but replaces the pixel with a pixel of value proportional to a normal distribution of it’s neighbours – not explained well, I know, but you’ve probably skipped the online reference and you need to read that to understand the way the filter works properly.

Median filter: The pixel is replaced with the median of it and its adjacent neighbours. This removes noise and preserves boundaries better than simple mean filtering, but can look odd. (The menu item “Process/Noise/Despeckle” is a 3×3 median filter).




Sigma filter: A modification on the standard mean filter but preserves edges better – can be though of as a “gentle smooth”. This filter will have to be downloaded. The user specifies the kernel size, the Sigma width and the minimum number of pixels to include. A Sigma value for the kernel is calculated (based on the variance and mean of the intensities) and only pixels within this Sigma range (= Sigma × the user defined Sigma Width scaling factor) are used to calculate the mean. If there are too few pixels (exact number set in the user dialog:Minimum number of pixels) in the kernel that are within the Sigma range then the central pixel which is assumed to be spuriously low or high and the mean of the rest of the kernel is taken. Increasing theSigma width and the minimum number of pixels results in increased smoothing and loss of edges.


Anisotropic Diffusion. This is an edge preserving smoothing filter. It will have to be downloaded.

Anisotropic diffusion filter.jpg 

Background correction

Background correction can be done in several ways and is facilitated if the grey image has the “Image/Lookup Tables/HiLo” LUT loaded. This displays the zero values blue and the 255 white values red.

If the background is relatively even across the image, it is most simply remove with the Brightness/Contrast command – slowly raise the Minimum value until most of the background is displayed blue. The press the Apply button to change the grey-values and remove the background.

Rolling-Ball background correction

For uneven background the menu command “Process/Subtract background” can be used. This menu command removes uneven background from images using a “rolling ball” algorithm. The radius should be set to at least the size of the largest object that is not part of the background. It can also be used to remove background from gels where the background is white. Running the command several times may produce better results. The user can choose whether or not to have a light background, create a background (no subtraction), have a sliding paraboloid, disable smoothing, or preview the results. The default value for the rolling ball radius is 50 pixels.

 RAW   Process/Subtract Background…”




Bright contr roll ball.jpg Histogram roll ball.jpg

Bright contr control roll ball.jpg

ROI background correction





Before correction
 Background intensity over time
After “ROI_BG_Correction
Roi back corr before.gif Roi back corr during.gif Roi back corr after.gif


Flat-field correction

Proper correction


Flat field correction.gif

1. Open both experimental image and flat-field image.





Calculator plus flat field.jpg









FFT background correction




Masking unwanted regions

Simple masking



Complex masking






