Some experiments with simple image processing algorithms
This is a small repository of some of my experiments with image processing. The
algorithms are nothing special and can probably be found in Wikipedia as
pseudocode, but it was very interesting for me to implement them and combine
them to solve a specific problem for a university assignment.
Examples
Histogram normalization
Basically, whenever the levels of gray in an image are clumped close together,
it makes sense to spread them throughout the [0, 255] range. This often takes
care of excessive brightness or darkness.
Info.
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Blurring
Two kinds of blurring are implemented, a simple mean blur and a gaussian blur.
The gaussian blur uses a fixed 3x3 kernel.
Info on mean, median and gaussian blurring.
| Mean blur with a radius of 3 (5x5 matrix) | ||
|---|---|---|
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| Gaussian blur | ||
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Edge detection
Two filters for edge detection are implemented, Laplacian and Sobel. The
results they give are quite different and can probably be used with varying
success on different occasions.
Info on LoG, and on
Sobel. The code for the
Sobel operator was taken almost as-is from Sau Sheong Chang’s
blog post
about it, so check that out as well.
| Laplacian over gaussian | ||
|---|---|---|
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| Sobel | ||
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Thresholding
There’s not much to explain about the simple thresholding by a given value. A
more interesting type of thresholding is the iterative one. Basically, it takes
an initial value and tries to threshold the image by that. The average
intensity of the foreground and background pixels is then used to perform
another threshold, and so on until it converges on a “best” value.
In cases with varying lighting, adaptive thresholding is better. The most
popular method for that seems to be Otsu’s, but for now, I’ve implemented a
simpler one. Each pixel is thresholded by the mean or by the median of the
surrounding pixels.
The Floyd-Steinberg algorithm for error propagation is used as an alternative
to the standard thresholding by a fixed value. I’ve yet to experiment with it
and expect to make it a bit more useful.
Info on thresholding in general and on adaptive thresholding. Info on iterative (or automatic) thresholding can be found on wikipedia.
| Adaptive thresholding | ||
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