# Foundations of Digital Image ## Digitization Process

A digitization process is often used to convert analog data, such as media, sound, image, and text, into a numerical representation through two discrete steps:

Sampling and Quantization.

First step, data is sampled at regular intervals, such as the grid of pixels used to represent a digital image. The frequency of sampling is referred to as resolution of the image. Sampling turns continuous data (analog) into discrete (digital) data. This is data occurring in distinct units: people, pages of a book, pixels.

Second, each sample is quantified, i.e. assigned a numerical value drawn from a defined range (such as 0-255 in the case of a 8-bit gray scale image).

What does QUANTIZATION look like?

Any image or audio, like color, projects a signal of its wavelength. The signals are measured through a y=sin(x) graph. It is a mathematical representation that becomes digitized when sampled by a computer.

The digital representation can change depending on its selected resolution. The higher the resolution, the more accurately the digital representation will measure the signal.

Although, the digitalization process reads analog and old media as continuous, they often combine discrete and continuous coding. The discrete coding in old media arises out of the Industrial Revolution and the Fordist Production Structure; the division of labor through assembly lines to create quick, efficient and standardized parts are all properties of discrete coding. This standardization logic is visible on the very font of this page, or even before, with the fonts of the first typewriters in the 1880s.  We can look at this current digitization process just as a continuation of this standardization, to precisely convert data to its own coding.

The image below illustrates how a continuous curve is defined by samples and represented by numbers: Also the image below shows how a continuous curve is represented in 2, 3 and 4-bit digital formats. To summarize, sampling refers to considering the image only at a finite number of points and quantization refers to the representation of the color value (in RGB format) at each sampled point using a finite number of bits. In this case, each image sample is called a pixel and every pixel has one and only one color value. Any typical desktop image scanner does sampling quantization. Usually, in scanning a printed image, the first steps are about the sampling area and rate and the later steps deal with the quantization parameters, such as resolution and file size.

Digitization should not only be seen as a technical process because it also has an important semiological and cultural significance. In his seminal book Language of the New Media, Lev Manovich states,

“While some old media such as photography and sculpture is truly continuous, most involve the combination of continuous and discrete coding. One example is motion picture film: each frame is a continuous photograph, but time is broken into a number of samples (frames). Video goes one step further by sampling the frame along the vertical dimension (scan lines). Similarly, a photograph printed using a halftone process coming discrete and continuous representations. Such photographs consist from a number of orderly dots (i.e., samples), however the diameters and areas of dots vary continuously. As this last example demonstrates, while old media contains level(s)  of discrete representations, the samples were never quantified. This quantification of samples is the crucial step accomplished by digitization. But why, we may ask, modern media technologies were often in part discrete? The key assumption of modern semiotics is that communication requires discrete units. Without discrete units, there is no language. As Roland Barthes has put it, language is, as it were, that which divides reality (for instance the continuous spectrum of the colors is verbally reduced to a series of discontinuous terms).”

Discrete representation of continuous analog media allows a communication through these units. Once something is numerically represented, the representation can take a different form. For example, once a piece of sound is numerically represented through a digitization process, then this numeric system can be used to also represent a color.