Help! There is a comet in my computer! 21
4 Recorded image and displayed image
We assumed at the beginning of our calculation of comet parameters that we recorded an
image of a comet with a camera. We worked with the pixel grey values of the original
recorded image that are stored in the image file. However, when we are measuring comets,
we have no direct access to the grey value data – instead of the numbers, the computer
shows us an image on the screen.
When an image of a comet is shown on the screen, what we really see is a reconstruction
of the recorded image that the computer creates from the file where all grey values of the
recorded image are stored. Recording of an image is also called image grabbing or image
acquisition. We will call the image that we recorded with the camera and is now saved in
the computer memory the grabbed image and the image that we see on the screen the
displayed image. For our measurement, the important thing is the grabbed image, because
it contains the grey values that represent light intensity that, in turn, represent the amount
of DNA on the slide.
The grabbed and the displayed image are not the same thing: what we see on the screen is
only a representation of the grabbed image. If we change the way that the image is
displayed on the screen, the file where the grey values for the grabbed image are stored is
not changed. If we enlarge or decrease the size of the displayed image by dragging its
corners, the grabbed image file does not change. If we change the brightness or the contrast
of the displayed image, the grabbed image does not change (Figure 12).
4.1 Look-up table (LUT)
Images of comets are composed of 256 different shades of grey; our eyes can distinguish
only a few dozens. Often a comet looks relatively dark on the image, and we are very bad
at differentiating dark shades of grey – we can hardly see the comet, although the computer
can easily measure it. We are much better at distinguishing colours than shades of grey.
We just found out that the displayed image can be different from the grabbed image. Can
this help us see?
Before we continue this debate, let us look at types of images with respect to colour.
Greyscale images are composed of different shades of grey (Figure 13A). In everyday life,
these images are called “black-and-white”. However, in image analysis we actually have a
special type of images that are truly only black (grey value 0) and white (grey value 255).
These images are binary images (Figure 13B; also called masks) and are used for
segmentation - to tell the computer which parts of the image are objects (ROI) that we wish
to measure (by definition shown in white) and which are other non-interesting parts of the
image (by definition shown in black). And we also have colour images (Figure 13C),
sometimes also called RGB images (RGB – red green blue).
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