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• Image Multiplier Online
• Image Multiplier Online
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Photomultiplier tubes (photomultipliers or PMTs for short), members of the class of vacuum tubes, and more specifically vacuum phototubes, are extremely sensitive detectors of light in the ultraviolet, visible, and near-infrared ranges of the electromagnetic spectrum.These detectors multiply the current produced by incident light by as much as 100 million times or 10 8 (i.e., 160 dB), in. Image Multiplier is an AddIn for Xamarin Studio. It adds a new file type '.multiplier' in which you can specify a set of output image files that you want to create and a set of source SVG files you want to process. Image Multiplier processes each source SVG file against each matched set of output specifiers to create PNG files.

Brief Description

Like other image arithmetic operators, multiplication comes in twomain forms. The first form takes two input images and produces anoutput image in which the pixel values are just those of the firstimage, multiplied by the values of the corresponding values in thesecond image. The second form takes a single input image and producesoutput in which each pixel value is multiplied by a specified constant.This latter form is probably the more widely used and is generallycalled scaling.

This graylevel scaling should not be confused withgeometric scaling.

How It Works

The multiplication of two images is performed in the obvious way in asingle pass using the formula:

Scaling by a constant is performed using:

Note that the constant is often a floating point number, and may beless than one, which will reduce the image intensities. It may even benegative if the image format supports that.

If the pixel values are actually vectors rather than scalar values(e.g. for color images) then the individual components (e.g. ref{rgb}{red, blueand green components}) are simply multiplied separately to produce theoutput value.

If the output values are calculated to be larger than the maximumallowed pixel value, then they may either be truncated at that maximumvalue, or they can `wrap around' and continue upwards from the minimumallowed number again.

Guidelines for Use

There are many specialist uses for scaling. In general though, given ascaling factor greater than one, scaling will brighten an image. Givena factor less than one, it will darken the image. Scaling generallyproduces a much more natural brightening/darkening effect than simplyadding an offset to the pixels, since it preserves therelative contrast of the image better. For instance,

shows a picture of model robot that was takenunder low lighting conditions. Simply scaling every pixel by a factorof 3, we obtain

which is much clearer. However, when using pixel multiplication, we should make sure that the calculated pixel values don't exceed the maximum possible value. If we, for example, scale the above image by a factor of 5 using a 8-bit representation, we obtain

All the pixels which, in the original image, have a value greater than 51 exceed the maximum value and are (in this implementation) wrapped around from 255 back to 0.

The last example shows that it is important to be aware of whatwill happen if the multiplications result in pixel values outside therange that can be represented by the image format being used. It is alsovery easy to generate very large numbers with pixel-by-pixelmultiplication. If the image processing software supports it, it isoften safest to change to an image format with a large range, e.g.floating point, before attempting this sort of calculation.

Scaling is also often useful prior to other image arithmetic in orderto prevent pixel values going out of range, or to prevent integerquantization ruining the results (as in integer imagedivision).

Pixel-by-pixel multiplication is generally less useful, althoughsometimes a binary image can be used to multiply another image inorder to act as a mask. The idea is to multiply by 1 thosepixels that are to be preserved, and multiply by zero those that arenot. However for integer format images it is often easier and fasterto use the logical operator AND instead.

Another use for pixel by pixel multiplication is to filter images in the frequency domain. We illustrate the idea using the example of

Image Multiplier online, free

First,we obtain

by applying the Fourier transform to the original image, and then we use pixel multiplication to attenuate certain frequencies in the Fourier domain. In this example we use a simple lowpass filter which (as a scaled version) can be seen in

The result of the multiplication is shown in

Finally,an inverse Fourier transform is performed to return to the spatial domain. The final result

shows the smoothing effect of a lowpass filter. More details and examples are given in the worksheets dealing with frequency filtering.

Interactive Experimentation

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You can interactively experiment with this operator by clicking here.

Exercises

1. Overlay

   and its skeleton

   using pixel addition (the skeletonwas derived from

   which was produced bythresholding the input image at 110). Use imagemultiplication to scale the images prior to the addition in order toavoid the pixel values being out of range. What effect does this haveon the contrast of the input images.

2. Use thresholding to segment the simple image

   into foreground and background. Use scaling to set theforeground pixel value to 2, and the background pixel value to 0. Thenuse pixel-by-pixel multiplication to multiply this image with theoriginal image. What has this process achieved and why might it beuseful?

References

Image Multiplier Online

E. DaviesMachine Vision: Theory, Algorithms andPracticalities, Academic Press, 1990, Chap. 2.

A. MarionAn Introduction to Image Processing, Chapmanand Hall, 1991, p 244.

Local Information

Image Multiplier Online

Specific information about this operator may be foundhere.

More general advice about the local HIPR installation is available in theLocal Information introductory section.

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©2003 R. Fisher, S. Perkins, A. Walker and E. Wolfart.