# Introduction to Video and Image Processing

## Introduction to Video and Image Processing

If you look at the image in Fig. 1.1 you can see three children. The two oldest children look content with life, while the youngest child looks a bit puzzled. We can detail this description further using adjectives, but we will never ever be able to present a textual description, which encapsulates all the details […]

## Image Acquisition (Introduction to Video and Image Processing) Part 1

Before any video or image processing can commence an image must be captured by a camera and converted into a manageable entity. This is the process known as image acquisition. The image acquisition process consists of three steps; energy reflected from the object of interest, an optical system which focuses the energy and finally a […]

## Image Acquisition (Introduction to Video and Image Processing) Part 2

The Image Sensor The light reflected from the object of interest is focused by some optics and now needs to be recorded by the camera. For this purpose an image sensor is used. An image sensor consists of a 2D array of cells as seen in Fig. 2.13. Each of these cells is denoted a […]

## Color Images (Introduction to Video and Image Processing) Part 1

So far we have restricted ourselves to gray-scale images, but, as you might have noticed, the real world consists of colors. Going back some years, many cameras (and displays, e.g., TV-monitors) only handled gray-scale images. As the technology matured, it became possible to capture (and visualize) color images and today most cameras capture color images. […]

## Color Images (Introduction to Video and Image Processing) Part 2

The RGB Color Space According to Eq. 3.1a color pixel has three values and can therefore be represented as one point in a 3D space spanned by the three colors. If we say that each color is represented by 8-bits, then we can construct the so-called RGB color cube, see Fig. 3.7. In the color […]

## Color Images (Introduction to Video and Image Processing) Part 3

Other Color Representations From a human perception point of view the triangular representation in 3.10(b) is not intuitive. Instead humans rather use the notion of hue and saturation, when perceiving colors. The hue is the dominant wavelength in the perceived light and represents the pure color, i.e., the colors located on the edges of the […]

## Point Processing (Introduction to Video and Image Processing) Part 1

Sometimes when people make a movie they lower the overall intensity in order to create a special atmosphere. Some overdo this and the result is that the viewer cannot see anything except darkness. What do you do? You pick up your remote and adjust the level of the light by pushing the brightness button. When […]

## Point Processing (Introduction to Video and Image Processing) Part 2

Exponential Mapping The exponential mapping uses a part of the exponential curve. It can be expressed as where k is a parameter that can be used to change of shape of the transformation curve and c is a scaling constant that ensures that the maximum output value is 255. It is calculated as where umax […]

## Point Processing (Introduction to Video and Image Processing) Part 3

Histogram Equalization Histogram equalization is based on non-linear gray-level mapping using a cumulative histogram. Table 4.1 A small histogram and its cumulative histogram. i is the bin number, H[i] the height of bin i, and C[i] is the height of the ith bin in the cumulative histogram i 0 1 2 3 H [i] 1 […]

## Point Processing (Introduction to Video and Image Processing) Part 4

Automatic Thresholding: Global Method As mentioned above, thresholding is based on the notion that an image consists of two groups of pixels; those from the object of interest (foreground) and those from the background. In the histogram these two groups of pixels result in two “mountains” denoted modes. We want to select a threshold value […]