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Lecture 2: Image Processing Review, Neighbors, Connected Components, and Distance c Bryan S. Morse, Brigham Young University, 1998–2000 Last modified on January 6, 2000 at 3:00 PM Reading SH&B, Chapter 2 2.1 2.1.1 Review of CS 450 Image Basics Image Domains An image (picture) can be thought of as being a function of two spatial dimensions: f (x, y) (2.1) For monochromatic images, the value of the function is the amount of light at that point. Sometimes, we can go to even higher dimensions with various imaging modalities. Medical CAT and MRI scanners produce images that are functions of three spatial dimensions: f (x, y, z) (2.2) f (x, y, t) (2.3) An image may also be of the form (x and y are spatial dimensions; t is time.) Since the image is of some quantity that varies over two spatial dimensions and also over time, this is a video signal, animation, or other time-varying picture sequence. Be careful—although both volumes and time-varying sequencies are three-parameter types of images, they are not the same! For this course, we’ll generally stick to static, two-dimensional images. The Varying Quantities The values in an image can be of many types. Some of these quantities can be scalars: • Monochromatic images have a single light intensity value at each point. Sometimes, these scalars don’t correspond to quantities such as light or sound: • In X-ray imaging, the value at each point corresponds to the attenuation of the X-ray beam at that position (i.e., not the radiation that gets through but the amount that doesn’t get through). • In one form of MR imaging, the value at each point indicates the number of single-proton atoms (i.e., hydrogen) in that area. • Range images encode at each point in an image the distance to the nearest object at that point, not it’s intensity. (Nearer objects are brighter, farthe