In order to become suitable for digital processing, an image function f(x,y) must be digitized both spatially and in amplitude. Typically, a frame grabber or digitizer is used to sample and quantize the analogue video signal. Hence in order to create an image which is digital, we need to covert continuous data into digital form. There are two steps in which it is done:
The sampling rate determines the spatial resolution of the digitized image, while the quantization level determines the number of grey levels in the digitized image. A magnitude of the sampled image is expressed as a digital value in image processing. The transition between continuous values of the image function and its digital equivalent is called quantization.
The number of quantization levels should be high enough for human perception of fine shading details in the image. The occurrence of false contours is the main problem in image which has been quantized with insufficient brightness levels.
In this lecture we will talk about two key stages in digital image processing. Sampling and quantization will be defined properly. Spatial and grey-level resolutions will be introduced and examples will be provided. An introduction on implementing the shown examples in MATLAB will be also given in this lecture.
Extra materials on sampling and quantization is available as the attachment (Prof. Paul Cuff, Princeton University).