3.2 
Commercial And Publicly
Available Digital Image
Processing Systems
John R. Jensen
Department of Geography
University of South Carolina
Columbia, South Carolina 29208
Direct Comments to: jrjensen@sc.edu

 

Introduction

Many commercial companies provide and actively market digital image processing systems. Some companies provide only the software, while others provide both propietary hardware and software. Public Government agencies such as NASA, NOAA, and the Bureau of Land Management as well as universities such as Purdue and Clark Universities have also developed digital image processing software. Most public systems are available at minimal cost. Several of the most widely used and commercial and publicly available digital image processing systems and their associated capabilities are summarized in Table 1.
  • Digital Image Processing Consultants and Software Distributors

    • Image Processing System Considerations

    When working with or selecting a digital image processing system the following factors should be considered: Figure 3-1 depicts a typical networked digital image processing laboratory configuration and peripheral devices for the input as well as hardcopy output of remotely sensed data. These elements are discussed in further detail throughout this module.
    Figure 3-1 
    Hypothetical 
    Workstation Network
     

    Number of Analysts and Mode of Operation

    A number of analysts must often have access to the image processing facilities, especially in an educational or research laboratory environment. Consequently, the number of analysts assigned to each workstation may range from one, which is exceptional, to perhaps five, which is inadequate (Sader and Winne, 1991). Furthermore, it is ideal if the image processing takes place in an interactive environment where the analyst selects the processes to be performed using a graphical user interface, or GUI (Campbell and Cromp, 1990). Most sophisticated image processing systems are designed with a friendly, point-and-click GUI that allows rapid selection and deselection of images to be analyzed and the appropriate functions to be applied.

    In most work environments, digital image processing workstations are networked to each other. This configuration allows the analyst at a workstation to (1) obtain a copy of the remote sensor data and applications programs from the file server and process it independently at the workstation and (2) access any peripheral on the local area network. Each workstation has its own central processing unit (CPU) and image processor memory that stores the remotely sensed displayed on the CRT screen. This allows very rapid digital image processing to take place.

    Central Processing Unit (CPU)

    Digital image processing of remote sensor data requires a large number of central processing unit (CPU) operations. The CPU is burdeneed with two major tasks: numerical calculations and input-output to peripheral mass storage devices, color monitors, printers, and the like. Therefore, it is necessary to have a CPU that can manage data efficiently.

    Operating System and Compiler

    The operating system and compiler must be easy to use yet powerful enough so that analysts may program their own algorithms and experiment with them on the system. It is not wise to configure an image processing system around an unusual operating system because it becomes difficult to communicate with certain devices and to share applications with other scientists. Most workstations use the UNIX operating system, while most personal computers use DOS, Windows, or Windows NT. UNIX has exceptional networking capabilities and allows wasy access to a variety of peripherals.

    The compilers most often used in the development of digital image processing software are BASIC, Assembler, C, and FORTRAN. Many digital image processing systems provide a toolkit that more sophisticated analysts can use to compile their own digital image processing algorithms. The toolkit usually consists of primitive subroutines, such as reading a line of image data into core, displaying a line of data to the CRT screen, or writing the modified line of data to the hard disk.

    Mass Storage

    Digital remote sensor data are usually stored in a matrix format with the various multispectral bands (e.g., blue, green, red, and reflective infrared) in geometric registration one to another. Each picture element (pixel) of each band is usually represented in the computer by a single 8-bit byte (a value from 0 to 255). It is often desirable to make the remotely sensed data available to the CPU for immediate processing. The best way to do this is to plce the data on a ard disk where each pixel of the data matrix may be accessed at random and at great speed. For example, it is common to place a full SPOT multispectral scene consisting of three bands (each 3000 x 3000) on the hard disk. This requires 27Mb of storage space on the hard disk. Most workstation systems are now routinely configured with gigabytes of hard disk storage.

    Image analysts have discovered that optical storage technologies now provide high-capacity, removable, direct-access, mass-storage devices.Optical disks can be written to, read, and written over again at very high speed. The technology used in rewritable optical systems is magnetooptics (MO), more accurately described as magnetically assisted optical recording. Optical disks can store gigabytes of data and represent an efficient storage media for archiving large collections of scanned aerial photgraphy or other types of remote sensor data. Much of the remote sensor data provided by SPOT Image Corporation and EOSAT are now distributed on optical disk media.

    In addition to optical and hard disks, it is possible to use 9-track tapes (1600 and 6250 bpi), 1/4" tape, 4 or 8mm tape, or floppy disks to:

    1. provide data input to the system
    2. back-up the hard or optical disks
    3. transfer data between workstations when a network is not in place
    4. archive image data sets or applications software once a project is completed
     

    CRT Screen Display Resolution

    The image processing system should be able to display at least 512x512 pixels and preferably more (e.g., 1024x1024) on the CRT screen at one time. This allows larger geographic areas to be examined at one time and places the terrain of interest in its regional context. Most Earth scientists prefer this regional perspective when performing terrain analysis using remote sensor data. Furthermore, it is disconcerting to have to analyze four 512x512 images when a single 1024x1024 display provides the information at a glance.

    CRT Screen Color Resolution

    This refers to the number of gray-scale tones or colors (e.g., 256) that may be displayed on a CRT monitor at one time out of a palette of available colors (e.g., 16.7 million). For many applications, such as high-contrast black-and-white linework cartography, only 1 bit of color is required [i.e., either the line is black or white (0 or 1)]. For more sophisticated computer graphics for which many shades of gray or different color combinations are required, up to 8 bits (or 256 colors) may be required (Preston, 1991). Most thematic mapping and GIS applications may be performed quite well by systems that display just 64 user-selectable colors out of a palette of 256 available colors.

    Image Processor Memory Required to Produce Various
    Numbers of Displayable Colors.

    Image Processor
    Memory (bits)

    Maximum Number of
    Colors Displayable at One
    Time on the CRT screen
    1 2 (B&W)
    2 4
    3 8
    4 16
    5 32
    6 64
    7 128
    8 256
    9 512
    10 1,024
    11 2,048
    12 4,096
    13 8,192
    14 16,384
    15 32,768
    16 65,536
    17 131,072
    18 262,144
    24 16,777,216
     

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    References

    Campbell, W. J. and R. F. Cromp, 1990, "Evolution of an Intelligent Information Fusion System, " Photogrammteric Engineering and Remote Sensing, 56(6):867-870.

    Jensen, J. R., 1996, Introductory Digital Image Processing: A remote sensing perspective, 2nd Edition. NJ: Prentice-Hall, pp. 66-67.

    Preston, K., 1991, "Who Needs 24-Bit Color?" Photonics Spectra 25(4):119-121.

    Sader, S. A. and J. C. Winne, 1991, "Digital Image Analysis Hardware/Software Use at U.S. Forestry Schools," Photogrammetric Engineering and Remote Sensing, 57(2):209-211.