3. What are the components of an Image Processing System?

Monday, 4 March 2013

3. What are the components of an Image Processing System?



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Components of an Image Processing System:

As recently as the mid-1980s, numerous models of image processing systems being sold
throughout the world were rather substantial peripheral devices that attached to equally
substantial host computers. Late in the 1980s and early in the 1990s, the market shifted to image
processing hardware in the form of single boards designed to be compatible with industry
standard buses and to fit into engineering workstation cabinets and personal computers. In
addition to lowering costs, this market shift also served as a catalyst for a significant number of
new companies whose specialty is the development of software written specifically for image
processing.

Although large-scale image processing systems still are being sold for massive
imaging applications, such as processing of satellite images, the trend continues toward
miniaturizing and blending of general-purpose small computers with specialized image
processing hardware. Figure 3 shows the basic components comprising a typical general-purpose system used for digital image processing. The function of each component is discussed in the following paragraphs, starting with image sensing.

With reference to sensing, two elements are required to acquire digital images. The first is a
physical device that is sensitive to the energy radiated by the object we wish to image. The
second, called a digitizer, is a device for converting the output of the physical sensing device into
digital form. For instance, in a digital video camera, the sensors produce an electrical output
proportional to light intensity. The digitizer converts these outputs to digital data.

Specialized image processing hardware usually consists of the digitizer just mentioned, plus
hardware that performs other primitive operations, such as an arithmetic logic unit (ALU), which
performs arithmetic and logical operations in parallel on entire images. One example of how an
ALU is used is in averaging images as quickly as they are digitized, for the purpose of noise
reduction. This type of hardware sometimes is called a front-end subsystem, and its most
distinguishing characteristic is speed. In other words, this unit performs functions that require
fast data throughputs (e.g., digitizing and averaging video images at 30 framess) that the typical
main computer cannot handle.

                         Fig.3. Components of a general purpose Image Processing System

The computer in an image processing system is a general-purpose computer and can range from
a PC to a supercomputer. In dedicated applications, some times specially designed computers are
used to achieve a required level of performance, but our interest here is on general-purpose image processing systems. In these systems, almost any well-equipped PC-type machine is
suitable for offline image processing tasks.

Software for image processing consists of specialized modules that perform specific tasks. A
well-designed package also includes the capability for the user to write code that, as a minimum,
utilizes the specialized modules. More sophisticated software packages allow the integration of
those modules and general-purpose software commands from at least one computer language.

Mass storage capability is a must in image processing applications. An image of size 1024*1024
pixels, in which the intensity of each pixel is an 8-bit quantity, requires one megabyte of storage
space if the image is not compressed. When dealing with thousands, or even millions, of images,
providing adequate storage in an image processing system can be a challenge. Digital storage for
image processing applications falls into three principal categories: (1) short-term storage for use
during processing, (2) on-line storage for relatively fast re-call, and (3) archival storage,
characterized by infrequent access. Storage is measured in bytes (eight bits), Kbytes (one
thousand bytes), Mbytes (one million bytes), Gbytes (meaning giga, or one billion, bytes), and
Tbytes (meaning tera, or one trillion, bytes). One method of providing short-term storage is
computer memory. Another is by specialized boards, called frame buffers, that store one or more
images and can be accessed rapidly, usually at video rates (e.g., at 30 complete images per
second).The latter method allows virtually instantaneous image zoom, as well as scroll (vertical
shifts) and pan (horizontal shifts). Frame buffers usually are housed in the specialized image
processing hardware unit shown in Fig.3.Online storage generally takes the form of magnetic
disks or optical-media storage. The key factor characterizing on-line storage is frequent access to
the stored data. Finally, archival storage is characterized by massive storage requirements but
infrequent need for access. Magnetic tapes and optical disks housed in “jukeboxes” are the usual
media for archival applications.

Image displays in use today are mainly color (preferably flat screen) TV monitors. Monitors are
driven by the outputs of image and graphics display cards that are an integral part of the
computer system. Seldom are there requirements for image display applications that cannot be
met by display cards available commercially as part of the computer system. In some cases, it is
necessary to have stereo displays, and these are implemented in the form of headgear containing
two small displays embedded in goggles worn by the user.

Hardcopy devices for recording images include laser printers, film cameras, heat-sensitive
devices, inkjet units, and digital units, such as optical and CD-ROM disks. Film provides the
highest possible resolution, but paper is the obvious medium of choice for written material. For
presentations, images are displayed on film transparencies or in a digital medium if image
projection equipment is used. The latter approach is gaining acceptance as the standard for image
presentations.

Networking is almost a default function in any computer system in use today. Because of the
large amount of data inherent in image processing applications, the key consideration in image
transmission is bandwidth. In dedicated networks, this typically is not a problem, but
communications with remote sites via the Internet are not always as efficient. Fortunately, this
situation is improving quickly as a result of optical fiber and other broadband technologies.

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