Basics of Image Processing

Now that we're acquainted ourselves with the medium through which we can acquire digital images, let's talk about what digital images are and what we can do to them.

So what is a digital image? Well, you can basically think of it as a 2x2 matrix or grid on which a bunch of brightness values are stored. If you remember from our previous discussions, the slots in this matrix are called pixels, and we typically encode the brightness values as a triplet of R, G, B values. So if you were to imagine a 3D coordinate space, you'll have the x, and the y axis defining the plane on which the image lies, and the z axis will represent the brightness values at each point, where higher the z value, the brighter the pixel is.

The real cool thing about having a discrete value matrix at hand is that we can now use simple math to apply some interesting effects to the image. The most obvious thing you can think of is taking the intensity values of an image and simply multiplying them by a factor.

For example, you can half the intensity values at all the pixels to get a image that is half the brightness. This is called image processing, and the particular operation we just described is called filtering. Filtering basically takes a pixel on an image, applies a certain mathematical function on it to yield a potentially different value and replaces the original with it. You can obivously repeat this process for all the pixels on a given image.

There's also another type of image processing called warping. In the case of warping, we take the intensity values found on a certain pixel and move them to another pixel. The most common example of warping is scaling.

The important thing to note here for both of these types of image processing techniques is that the function used for the process only takes into consideration the intensity value of a single pixel. In

other words, it is agnostic to the values of intensity foudn in any other pixesl in a given image. These types of image processing is called point processing. So, in point processing the effect of the function applied to one point has no impact on any other points as all points are processed independentl of one another.

In the next entry, we'll talk about specific examples of filters.