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Much of image processing is about simplifying images. It is often useful to simplify images by reducing the number of colors or grey values (see also comics). Images with fewer colors can be compressed to take up less space on disk and download faster over a network. Images with fewer colors are also less expensive to print. One problem with reducing an image's colors is that it's easy to lose too much of the high-frequency edge information that people need to identify the subject of the image. |
 mean shift |
Another way to simplify images is by
identifying edges. I recently ported (from C++ to Java) publically-available
edge detection algorthms that are part of the Rutgers University “mean
shift” EDISON
system (Edge Detection and Image Segmentation) . You can get the code here. |
 imagebrowser |
I wrote a Java image browser for viewing and filtering image collections on local or remote media with a special interface to Google's image search that only displays Web images that are immediately available. |
 dynamic threshold |
I have used variations of dynamic thresholding for creating very small icons of faces and for simplifying images to make them look more like comics. Dynamic thresholding uses a lower threshold in dark areas of the image and a higher threshold in light areas of the image. In most cases, dynamic thresholding does a good job of preserving high-frequency details such as edges, even in images with uneven illumination where edges may move through both light and dark areas of the image.
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