am ch.3 digital image processing: hardware and system considerations

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Ch.3 Digital Image Processing: Hardware and System Considerations


Image Processing System Considerations

Digital remote sensor data are analyzed using a digital image processing system that consists of computer hardware and special-purpose image processing software. This lecture describes:

fundamental digital image processing system hardware characteristics,

digital image processing software (computer program) requirements, and

public and commercial sources of digital image processing hardware and software



A digital image processing system should:

• have a reasonable learning curve and be easy to use,

• have a reputation for producing accurate results (ideally the company has ISO certification),

• produce the desired results in an appropriate format (e.g., map products in a standard cartographic data structure compatible with most GIS), and

• be within the department’s budget


Computer Systems and Peripheral Devices in A

Typical Digital Image Processing

Laboratory


Image Processing System Hardware /Software Considerations

• Number and speed of Central Processing Unit(s) (CPU)

• Operating system (e.g., Microsoft Windows; UNIX, Linux, Macintosh)

• Amount of random access memory (RAM)

• Number of image analysts that can use the system at one time and mode of operation (e.g., interactive or batch)

• Serial or parallel image processing

• Arithmetic coprocessor or array processor

• Software compiler(s) (e.g., C++, Visual Basic, Java)


Image Processing System Hardware /Software Considerations

• Type of mass storage (e.g., hard disk, CD-ROM, DVD) and amount (e.g., gigabytes)

• Monitor display spatial resolution (e.g., 1024 768 pixels)

• Monitor color resolution (e.g., 24-bits of image processing video memory yields 16.7 million displayable colors)

• Input devices (e.g., optical-mechanical drum or flatbed scanners, area array digitizers)

• Output devices (e.g., CD-ROM, CD-RW, DVD-RW, film-writers, line plotters, dye sublimation printers)

• Networks (e.g., local area, wide area, Internet)


Central Processing Unit

The central processing unit (CPU) is the computing part of the computer. It consists of a control unit and an arithmetic logic unit. The CPU performs:

• numerical integer and/or floating point calculations, and

• directs input and output from and to mass storage devices, color monitors, digitizers, plotters, etc.


Central Processing Unit

A CPU’s efficiency is often measured in terms of how many millions-of-instructions-per-second (MIPS) it can process, e.g., 500 MIPS.

It is also customary to describe a CPU in terms of the number of cycles it can process in 1 second measured in megahertz, e.g., 1000 Mhz (1 GHz).

Manufacturers market computers with CPUs faster than 4 GHz, and this speed will increase. The system bus connects the CPU with the main memory, managing data transfer and instructions between the two. Therefore, another important consideration when purchasing a computer is bus speed.


Moore’s Law

In 1985, Gordon Moore was preparing a speech and made an observation. He realized that each new computer CPU contained roughly twice as much capacity as its predecessor and each CPU was released within 18 to 24 months of the previous chip. If this trend continued, he reasoned, computing power would rise exponentially over relatively brief periods of time. Moore’s law described a trend that has continued and is still remarkably accurate. It is the basis for many planners’ performance forecasts. MIPS has also increased logarithmically.


History of Intel Microprocessors

4004 Microprocessor used in the

Busicom Calculator

Busicom Calculator

Intel Pentium 4


Type of Computer:

* Personal Computers (32 to 64-bit CPU)

* Workstation (> 64-bit CPU)

* Mainframe (> 64-bit CPU)

Type of Computer

Jensen, 2004Jensen, 2004

Personal computers (16- to 64-bit CPUs) are the workhorses of digital image processing and GIS analysis. Personal computers are based on microprocessor technology where the entire CPU is placed on a single chip. These inexpensive complex-instruction-set-computers (CISC) generally have CPUs with 32- to 64-bit registers (word size) that can compute integer arithmetic expressions at greater clock speeds and process significantly more MIPS than their 1980s – 1990s 8-bit predecessors. The 32-bit CPUs can process four 8-bit bytes at a time and 64-bit CPUs can process eight bytes at a time.

Jensen, 2004

Workstations usually consist of a >64-bit reduced-instruction-set-computer (RISC) CPU that can address more random access memory than personal computers. The RISC chip is typically faster than the traditional CISC. RISC workstations application software and hardware maintenance costs are usually higher than personal computer-based image processing systems. The most common workstation operating systems are UNIX and various Microsoft Windows products.

Type of Computer


Type of Computer

Mainframe computers (>64-bit CPU) perform calculations more rapidly than PCs or workstations and able to support hundreds of users simultaneously, especially parallel mainframe computers such as a CRAY. This makes mainframes ideal for intensive, CPU-dependent tasks (e.g., image rectification, mosaicking, filtering, classification, hyperspectral image analysis, and GIS modeling). If desired, the output from intensive mainframe processing can be passed to a workstation or personal computer for subsequent less intensive, inexpensive processing. Mainframe computer systems are expensive to purchase and maintain. Mainframe applications software is more expensive.


Operating System

The operating system is the first program loaded into random access memory (RAM) when the computer is turned on. It controls the computer’s higher-order functions. The operating system kernel resides in memory at all times. The operating system provides the user interface and controls multitasking. It handles the input and output to the hard disk and all peripheral devices such as compact disks, scanners, printers, plotters, and color displays. All digital image processing application programs must communicate with the operating system. The operating system sets the protocols for the application programs that are executed by it.


Read Only Memory and Random Access MemoryRead-only memory (ROM) retains information even

after the computer is shut down because power is supplied from a battery that must be replaced occasionally. Most computers have sufficient ROM for digital image processing applications; therefore, it is not a serious consideration.

Random access memory (RAM) is the computer’s primary temporary workspace. It requires power to maintain its content. Therefore, all of the information that is temporarily placed in RAM while the CPU is performing digital image processing must be saved to a hard disk (or other media such as a CD) before turning the computer off.


Interactive Graphical User Interface (GUI)

One of the best scientific visualization environments for the analysis of remote sensor data takes place when the analyst communicates with the digital image processing system interactively using a point-and-click graphical user interface (GUI). Most sophisticated image processing systems are now configured with a friendly GUI that allows rapid display of images and the selection of important image processing functions.


Graphical User Interface

Several effective digital image processing graphical user interfaces include:

• ERDAS Imagine’s intuitive point-and-click icons,

• Research System’s Environment for Visualizing Images (ENVI) hyperspectral data analysis interface,

• ER Mapper, • IDRISI, • ESRI ArcGIS Image Analyst, and • Adobe Photoshop.


ENVI Interface


ERDAS Interface


Interactive versus Batch Processing

Non-interactive, batch processing is of value for time-consuming processes such as image rectification, mosaicking, orthophoto creation, filtering, etc.

• Batch processing frees up lab PCs or workstations during peak demand because the jobs can be stored and executed when the computer is idle (e.g., early morning hours).

• Batch processing can also be useful during peak hours because it allows the analyst to set up a series of operations that can be executed in sequence without operator intervention.

• Digital image processing also can now be performed interactively over the Internet at selected sites.


Serial and Parallel Image Processing

It is possible to obtain PCs, workstations, and mainframe computers that have multiple CPUs that operate concurrently. Specially written parallel processing software can parse (distribute) the remote sensor data to specific CPUs to perform digital image processing. This can be much more efficient than processing the data serially.


Serial and Parallel Image Processing

Consider performing a per-pixel classification on a 1024 row by 1024 column remote sensing dataset. In the first example, each pixel is classified by passing the spectral data to the CPU and then progressing to the next pixel. This is serial processing. Conversely, suppose that instead of just one CPU we had 1024 CPUs. In this case the class of each of the 1024 pixels in the row could be determined using 1024 separate CPUs. The parallel image processing would classify the line of data about 1024 times faster than would processing it serially.


Compiler

A computer software compiler translates instructions programmed in a high-level language such as C++ or Visual Basic into machine language that the CPU can understand. A compiler usually generates assembly language first and then translates the assembly language into machine language. The compilers most often used in the development of digital image processing software are C++, Assembler, and Visual Basic. Many digital image processing systems provide a toolkit that programmers can use to compile their own digital image processing algorithms (e.g., ERDAS, ER Mapper, ENVI).


Storage and Archiving Considerations

Digital image processing of remote sensing and related GIS data requires substantial mass storage resources. Mass storage media should have:

• rapid access time, • longevity (i.e., last for a long time), and

be • inexpensive.


Rapid Access Mass Storage

Digital remote sensor data (and ancillary raster GIS data) are often stored in a matrix band sequential (BSQ) format in which each spectral band of imagery (or GIS data) is stored as an individual file. Each picture element of each band is typically represented in the computer by a single 8-bit byte with values from 0 to 255.

The best way to make brightness values rapidly available to the computer is to place the data on a hard disk, CD-ROM, DVD, or DVD-RAM where each pixel of the data matrix may be accessed at random (not serially) and at great speed (e.g., within microseconds). The cost of hard disk, CD-ROM, or DVD storage per gigabyte continues to decline.


Rapid Access Mass Storage

It is common for digital image processing laboratories to have gigabytes of hard-disk mass storage associated with each workstation. Many image processing labs now use RAID (redundant arrays of inexpensive hard disks) technology in which two or more drives working together provide increased performance and various levels of error recovery and fault tolerance. Other storage media, such as magnetic tapes, are usually too slow for real-time image retrieval, manipulation, and storage because they do not allow random access of data. However, given their large storage capacity, they remain a cost-effective way to archive digital remote sensor data.


Potential Longevity of

Remote Sensor Data

Storage Media


Archiving Considerations and Longevity

• Properly exposed, washed, and fixed analog black & white aerial photography negatives have considerable longevity, often more than 100 years.

• Color negatives with their respective dye layers have longevity, but not as much as the black-and-white negatives.

• Black & white paper prints have greater longevity than color prints (Kodak, 1995).

• Hard and floppy magnetic disks have relatively short longevity, often less than 20 years.

• Magnetic tape media (e.g., 3/4-in. tape, 8-mm tape) can become unreadable within 10 to 15 years if not rewound and properly stored in a cool, dry environment.


Archiving Considerations and Longevity

Only the optical disk provides relatively long-term storage potential (>100 years). In addition, optical disks store large volumes of data on relatively small media. Advances in optical compact disc (CD) technology promise to increase the storage capacity to > 17 Gb using new rewriteable digital video disc (DVD) technology. In most remote sensing laboratories, rewritable CD-RWs or DVD-RWs have supplanted tapes as the backup system of choice. DVD drives are backwards compatible and can read data from CDs.


Computer Display Spatial and Color Resolution

The display of remote sensor data on a computer screen is one of the most fundamental elements of digital image analysis. Careful selection of the computer display characteristics will provide the optimum visual image analysis environment for the human interpreter. The two most important characteristics are computer :

• display spatial resolution, and • color resolution.


Computer Screen Display Resolution

The image processing system should be able to display at least 1024 rows by 1024 columns on the computer screen at one time. This allows larger geographic areas to be examined 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 512 512 images when a single 1024 1024 display provides the information at a glance. An ideal screen display resolution is 1600 1200 pixels.


Computer Screen Color Resolution

The computer screen color resolution is the number of gray-scale tones or colors (e.g., 256) that can 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 l)]. For more sophisticated computer graphics for which many shades of gray or color combinations are required, up to 8 bits (or 256 colors) may be required. 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 colors.http://www.webstyleguide.com/graphics/displays.html


Important Image Processing Functions

Many of the most important functions performed using digital image processing systems are summarized in Table 3-4. Personal computers now have the computing power to perform each of these functions.


Image Processing System Functions

Preprocessing (Radiometric and Geometric)

Display and Enhancement

Information Extraction

Photogrammetric Information Extraction

Metadata and Image/Map Lineage Documentation

Image and Map Cartographic Composition

Geographic Information Systems (GIS)

Integrated Image Processing and GIS

UtilitiesJensen, 2004


Important Image Processing Functions

It is not good for remotely sensed data to be analyzed in a vacuum. Remote sensing information fulfills its promise best when used in conjunction with ancillary data (e.g., soils, elevation, and slope) stored in a geographic information system (GIS). The ideal system should be able to process the digital remote sensor data and perform any necessary GIS processing. It is not efficient to exit the digital image processing system, log into a GIS system, perform a required GIS function, and then take the output of the procedure back into the digital image processing system for further analysis. Integrated systems perform both digital image processing and GIS functions and consider map data as image data (or vice versa) and operate on them accordingly.


Selected Commercial and Public Digital Image Processing Systems(Jensen, 2004)


Selected Commercial and Public Digital Image Processing Systems

(Jensen, 2004)


Selected Commercial and Public Digital Image Processing Systems(Jensen, 2004)


Major Commercial Digital Image Processing Systems

ERDAS

Leica Photogrammetry Suite

ENVI

IDRISI

ER Mapper

PCI Geomatica

eCognition


Major Public Digital Image Processing Systems

GRASS

MultiSpec (LARS Purdue University)

C-Coast

Adobe Photoshop


Sources of Digital Image Processing Systems

ACORN, Atmospheric CORrection Now, www.aigllc.com/acorn/ intro.asp

AGIS Software, www.agismap.com

Applied Analysis Inc., Subpixel Processing, www.discover-aai.com

ArcGIS Feature Analyst; www.featureanalyst.com

ATCOR2, www.geosystems.de/atcor/atcor2.html

AUTOCAD, Autodesk, Inc., usa.autodesk.com

BAE Systems SOCET Set, www.socetset.com

Blue Marble Geographics, www.bluemarblegeo.com.

C-Coast, http://coastwatch.noaa.gov/cw_ccoast.html

Cosmic, www.openchannelfoundation.org/cosmic

DIMPLE, www.process.com.au/AboutDIMPLE.shtml

Dragon, Goldin-Rudahl Systems, www.goldin-rudahl.com

EarthView, Atlantis Scientific Systems, www.pcigeomatics.com

EIDETIC Earthscope, www.eidetic.bc.ca/~eidetic/es1.htm

ENVI, Research Systems, Inc., www.rsinc.com

ELAS (DIPIX, Datastar), http://technology.ssc.nasa.gov/PDFs/ SSC-00001_SS_NTTS.pdf

ERDAS Imagine, www.erdas.com

ER Mapper, www.ermapper.com

FullPixelSearch, www.themesh.com/elink13.html

Global Lab, Data Translation, 100 Locke Dr., Marlboro, MA 01752-1192

GRASS, http://grass.itc.it

IDRISI, Clarke University, www.clarklabs.org

ImagePro, www.i-cubeinc.com/software.htm

Intelligent Library System, Lockheed Martin, www.lmils.com

Intergraph, www.intergraph.com


Sources of Digital Image Processing Systems

MapInfo, www.mapinfo.com

MacSadie, www.ece.arizona.edu/~dial/base_files/software/ MacSadie1.2.html

MrSID, LizardTech, www.lizardtech.com

MultiSpec, www.ece.purdue.edu/~biehl/MultiSpec/.

NIH-Image, http://rsb.info.nih.gov/nih-image

NOeSYS, www.rsinc.com/NOESYS/index.cfm

PCI, www.pcigeomatics.com

PHOTOSHOP, www.adobe.com

RemoteView, www.sensor.com/remoteview.html

R-WEL Inc., www.rwel.com

TNTmips, MicroImages, www.microimages.com

VISILOG, www.norpix.com/visilog.htm

XV image viewer, www.trilon.com/xv

am ch.3 digital image processing: hardware and system considerations

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