3.2 Digital Media
Digital media take advantage of advances in computer-processing techniques and inherit their strength from digital signals. The following distinguishing features make them superior to the analog media:
Robustness–The quality of digital media will not degrade as copies are made. They are most stable and more immune to the noises and errors that occur during processing and transmission. Analog signals suffer from signal-path attenuation and generation loss (as copies are made) and are influenced by the characteristics of the medium itself.
Seamless integration–This involves the integration of different media through digital storage and processing and transmission technologies, regardless of the particular media properties. Therefore, digital media eliminate device dependency in an integrated environment and allow easy data composition of nonlinear editing.
Reusability and interchangeability–With the development of standards for the common exchange formats, digital media have greater potential to be reused and shared by multiple users.
Ease of distributed potential–Thousands of copies may be distributed electronically by a simple command.
Digital image Digital images are captured directly by a digital camera or indirectly by scanning a photograph with a scanner. They are displayed on the screen or printed.
Digital images are composed of a collection of pixels that are arranged as a 2D matrix. This 2D or spatial representation is called the image resolution. Each pixel consists of three components: red (R), green (G) and blue (B). On a screen, each component of a pixel corresponds to a phosphor. A phosphor glows when excited by an electron gun. Various combinations of different RGB intensities produce different colors. The number of bits to represent a pixel is called the color depth, which decides the actual number of colors available to represent a pixel. Color depth is in turn determined by the size of the video buffer in the display circuitry.
The resolution and color depth determine the presentation quality and the size of image storage. The more pixels and the more colors there are means the better the quality and the larger the volume. To reduce the storage requirement, three different approaches can be used:
Index color–This approach reduces the storage size by using a limited number of bits with a color lookup table (or color palette) to represent a pixel. Dithering can be applied to create additional colors by blending colors from the palette. This is a technique taking advantage of the fact that the human brain perceives the media color when two different colors are adjacent to one another. With palette optimization and color dithering, the range of the overall color available is still considerable, and the storage is reduced.
Color subsampling–Humans perceive color as brightness, hue and saturation rather than as RGB components. Human vision is more sensitive to variation in the luminance (or brightness) than in the chrominance (or color difference). To take advantage of such differences in the human eye, light can be separated into the luminance and chrominance components instead of the RGB components. The color subsampling approach shrinks the file size by down-sampling the chrominance components, that is, using less bits to represent the chrominance components while having the luminance component unchanged.
Spatial reduction–This approach, known as data compression, reduces the size by throwing away the spatial redundancy within the images.
3.2 Digital Media