This tutorial demonstrates a few of the image enhancement tools in AIP4Win. In it and those that follow, you will learn how to use these tools to extract detail from otherwise bland images. More than just producing "pretty pictures," these techniques can be used to enhance details and show structures that, because of their low contrast, would otherwise be invisible. Later tutorials show you which tools and processes to use on deep-sky and planetary images.
You may have noticed that the arrangement of the menus and the toolbar, the book itself, and to some extent these tutorials, is such that the flow moves through the following steps:
1. Bring an image into the program,
2. view information contained within the image file header,
3. calibrate the image,
4. make measurements on the image, and
5. enhance the image, including geometric transformations.
This is not accidental. This flow of operation is necessary to preserve scientifically useful information. Up to this point in the tutorials we have not made any changes to the information contained in the image other than to remove noise and uneven illumination effects caused by the optical system or sensitivity variation across the CCD detector.
The types of operations you will perform in this tutorial will, for the most part, modify the data in a non-linear manner, rendering them useless for photometric purposes. You will also be able to modify the spatial distribution of the data, reducing their astrometric validity. It is for this reason that we covered the measurement capabilities first, in keeping with this flow.
The types of operations you will exercise in this tutorial are some of the most fun capabilities of AIP4Win. With these enhancement tools you can make pretty pictures as well as display the hidden structure of astronomical objects you have imaged with your CCD camera. These operations work well on scanned photographs as well, and provide capabilities that just aren't possible in the darkroom.
A final note before starting: preserve your original files. You cannot "unen-hance" a processed image and recover the original data. Now, let's get started.
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