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J.Jensen
pression ratio of about 1: 10 for color photos without considerable degradation in
the visual or geometric quality of the image for photogrammetric applications
(Lammi and Sarjakoski, 1995). Unfortunately, such lossy data may be unsuitable
for scientists performing quantitative analysis of the data. Therefore, it is good
practice to store the archive image using a loss-less data compression algorithm
based on a) JPEG differential pulse code modulation - DPCM or b) run-length
encoding (e.g. the simple UNIX compress command) so that both novice users
and scientists have access to the best reproduction of the original data. The optimum lossy and/or loss-less image compression algorithm(s) are still being debated, e.g., fractal, wavelet, quadtree, run-length encoding (Russ, 1992; Pennebaker and Mitchell, 1993; Jensen, 1996; Nelson, 1996; Sayood, 1996). Robust
multiple frame video data compression algorithms now exist that are of benefit for
remote sensing image animation projects (e.g. MPEG).
The image processing system must have the capability to import and export remote sensing and GIS data files stored in a variety of standard formats. The system must be able to read at least the following file formats: encapsulated postscript file - EPSF, tagged interchange file format - TIFF, Macintosh PICT,
ERDAS, ESRI coverages, GeoTIFF, and CompuServe GIF.
3.3 Commercial and Publicly Available Digital Image Processing Systems
The development and marketing of digital image processing systems is a multimillion dollar industry. The image processing software/hardware may be used for
non-destructive evaluation of items on an assembly line, medical image diagnosis,
and/or analysis of remote sensor data. Some vendors provide only the software
while others provide both proprietary hardware and software. Several of the most
widely used systems that are used to analyze remotely sensed data are summarized
in Appendix 3.1. Their capabilities are cross-referenced to the general image processing functions summarized in Table 3.2.
Universities and public government agencies have developed digital image
processing software. Several of the most widely used and publicly available digital
image processing systems are summarized in Appendix 3.1. COSMIC at the University of Georgia is a clearinghouse for obtaining NASA sponsored digital image
processing software for the cost of media duplication.
3.4 Summary
Analysis of remotely sensed data and GIS information for hydrologic applications
requires access to sophisticated digital image processing system and geographic
information system software. This chapter identified typical a) computer hardware/software characteristics, b) image processing functions required to analyze
remote sensor data for hydrologic and water management applications, and c)
selected commercial and public digital image processing systems and their generic
functions available for earth resource mapping. The Earth Observing System
J.Jensen
pression ratio of about 1: 10 for color photos without considerable degradation in
the visual or geometric quality of the image for photogrammetric applications
(Lammi and Sarjakoski, 1995). Unfortunately, such lossy data may be unsuitable
for scientists performing quantitative analysis of the data. Therefore, it is good
practice to store the archive image using a loss-less data compression algorithm
based on a) JPEG differential pulse code modulation - DPCM or b) run-length
encoding (e.g. the simple UNIX compress command) so that both novice users
and scientists have access to the best reproduction of the original data. The optimum lossy and/or loss-less image compression algorithm(s) are still being debated, e.g., fractal, wavelet, quadtree, run-length encoding (Russ, 1992; Pennebaker and Mitchell, 1993; Jensen, 1996; Nelson, 1996; Sayood, 1996). Robust
multiple frame video data compression algorithms now exist that are of benefit for
remote sensing image animation projects (e.g. MPEG).
The image processing system must have the capability to import and export remote sensing and GIS data files stored in a variety of standard formats. The system must be able to read at least the following file formats: encapsulated postscript file - EPSF, tagged interchange file format - TIFF, Macintosh PICT,
ERDAS, ESRI coverages, GeoTIFF, and CompuServe GIF.
3.3 Commercial and Publicly Available Digital Image Processing Systems
The development and marketing of digital image processing systems is a multimillion dollar industry. The image processing software/hardware may be used for
non-destructive evaluation of items on an assembly line, medical image diagnosis,
and/or analysis of remote sensor data. Some vendors provide only the software
while others provide both proprietary hardware and software. Several of the most
widely used systems that are used to analyze remotely sensed data are summarized
in Appendix 3.1. Their capabilities are cross-referenced to the general image processing functions summarized in Table 3.2.
Universities and public government agencies have developed digital image
processing software. Several of the most widely used and publicly available digital
image processing systems are summarized in Appendix 3.1. COSMIC at the University of Georgia is a clearinghouse for obtaining NASA sponsored digital image
processing software for the cost of media duplication.
3.4 Summary
Analysis of remotely sensed data and GIS information for hydrologic applications
requires access to sophisticated digital image processing system and geographic
information system software. This chapter identified typical a) computer hardware/software characteristics, b) image processing functions required to analyze
remote sensor data for hydrologic and water management applications, and c)
selected commercial and public digital image processing systems and their generic
functions available for earth resource mapping. The Earth Observing System