Low cost frame averaging using Matrox Pulsar hardware on PCs
Internal floating point representation of all data means arithmetic and processing functions may be applied without concern
for image format i.e. a series of sums may be applied to a number of images and real values are
available for the results. Functions such as logs may be applied without creating large lookup
tables.
Automated acquisition, file naming and saving of images e.g. it is a simple task to save an average
of every n frames every x seconds leaving your hands free to concentrate on the experiment in hand.
Stack processing - Apply processing to a series of images with the same effort as a single image or
create graphs of density against time as simply as marking a region of interest.
Extremely flexible Pseudo colouring
Direct control of Cairn filter wheels.
Automated image alignment.
High play factor !- Applying arithmetic to images or stacks of images is just like using a calculator
i.e. to calculate the ratio of two images simply click on the first, click the divide button, click the
second image and then click the equals button. The resulting image will be scaled to make best
use of the grey scales available for display whilst maintaining the real values of the calculation. There is
no need to wade through stacks of dialog boxes and then worry about how the image is to be scaled to
fit another integer image. The following java applet gives some feeling for the ease of use.
Simply click on images and operations just like a calculator.
An object oriented expression evaluator transparently applies arithmetic and processing functions to
combinations of all data types. Currently supported data types are images, stacks of images,
1D data sets i.e. graphs and simple numerical values. It is equally valid to multiply an image by a
constant, an image or a graph. Translation between integer and floating point data is transparent.
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