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2.3
Digital Image Data Formats |
John R. Jensen
Steven R. Schill
Department of Geography
University of South Carolina
Columbia, South Carolina 29208
Direct Comments to: jrjensen@sc.edu
Introduction
In order to properly process
remotely sensed data, the analyst must know how the data is organized and
stored on digital tapes and how the data is processed by computers and
software. Understanding existing digital data formats is essential before
the data can be processed. There are many different data formats used for
storing digital remotely sensed data. Many commercial data suppliers such
as EOSAT and SPOT, provide radiometrically corrected data in a customer
specified format. There are four major data formats used by government
and comercial data suppliers:
-
Band Interleaved by Pixel (BIP) Format
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Band Interleaved by Line (BIL) Format
-
Band Sequential (BSQ) Format
-
Run-Length Encoding Format
Most digital data are stored on nine-track tape (800, 1600,
and 6250 bpi), 4- or 8-mm tape, or on optical disks. The nine-track and
4- or 8-mm tapes must be read serially while it is possible to randomly
select areas of interest from within the optical disk. This may result
in significant savings of time when unloading remote sensor data. The 4-
and 8-mm tape and compact disks are very efficient storage mediums, as
opposed to the large number of nine-track tapes required to store most
images (Jensen, 1996).
Band Interleaved By Pixel Format (BIP)
One of the earliest digital formats used for satellite data
is band interleaved by pixel (BIP) format. This format treats pixels as
the separate storage unit. Brightness values for each pixel are stored
one after another. It is practical to use if all bands in an image are
to be used. Figure 2-3.1 shows the logic of how the data is recorded to
the computer tape in sequential values for a four band image in BIP format.
| Figure 2-3.1 Band Interleaved by Pixel Format
(BIP) |
| Line 1 |
Pixel 1 |
Band 1 |
|
Line 1 |
Pixel 2 |
Band 1 |
|
Line 1 |
Pixel 3 |
Band 1 |
| Line 1 |
Pixel 1 |
Band 2 |
|
Line 1 |
Pixel 2 |
Band 2 |
|
Line 1 |
Pixel 3 |
Band 2 |
| Line 1 |
Pixel 1 |
Band 3 |
|
Line 1 |
Pixel 2 |
Band 3 |
|
Line 1 |
Pixel 3 |
Band 3 |
| Line 1 |
Pixel 1 |
Band 4 |
|
Line 1 |
Pixel 2 |
Band 4 |
|
Line 1 |
Pixel 3 |
Band 4 |
All four bands are written to the tape before values for
the next pixel are represented. Any given pixel located on the tape contains
values for all four bands written directly in sequence. This format may
be awkward to use if only certain bands of the imagery are needed. Often
data in BIP format is organized into four separate panels, or tiles, consisting
of vertical strips each 840 lines wide in the x direction and 2,342 lines
long in the y direction. In order to read all four bands of the image,
all four panels must be pieced together to form the entire scene (Campbell,
1987).
Band Interleaved By Line Format (BIL)
Just as the BIP format treats each pixel of data as the separate
unit, the band interleaved by line (BIL) format is stored by lines. Figure
2-3.2 shows the logic of how the data is recorded to the computer tape
in sequential values for a four band image in BIL format.
| Figure 2-3.2 Band Interleaved by Line Format
(BIL) |
| Line 1 |
Band 1 |
Line 1 |
Band 2 |
Line 1 |
Band 3 |
Line 1 |
Band 4 |
|
|
|
|
Line 2 |
Band 1 |
Line 2 |
Band 2 |
Line 2 |
Band 3 |
Line 2 |
Band 4 |
|
|
|
|
Line 3 |
Band 1 |
Line 3 |
Band 2 |
Line 3 |
Band 3 |
Line 3 |
Band 4 |
|
|
|
|
Line 4 |
Band 1 |
Line 4 |
Band 2 |
Line 4 |
Band 3 |
Line 4 |
Band 4 |
Each line is represented in all four bands before the
next line is recorded. Like the BIP format, it is a useful to use if all
bands of the imagery are to be used in the analysis. If some bands are
not of interest, the format is inefficient if the data are on tape, since
it is necessary to read serially past unwanted data.
Band Sequential Format
The band sequential format requires that all data for a single
band covering the entire scene be written as one file (see
Fig. 2-3.3). Thus, if an analyst wanted to extract the area in the
center of a scene in four bands, it would be necessary to read into this
location in four separate files to extract the desired information. Many
researchers like this format because it is not necessary to read serially
past unwanted information if certain bands are of no value, especially
when the data are on a number of different tapes. Random-access optical
disk technology, however, makes this serial argument obselete.
Run-Length Encoding
Run-length encoding is a band sequential format that keeps
track of both the brightness value and the number of times the brightness
value occurs along a given scan line. For example, if a body of water were
encountered with brightness values of 10 for 60 pixels along a scan line,
this could be stored in the computer in integer (213) format as 060010,
meaning that the following 60 pixels will each have a brightness value
of 10. Storing the two values 60 and 10 would require far less memory on
disk or tape than storing 60 number 10s. However. if the data are exceptionally
heterogeneous, with very few similar brightness values, this format is
no better than the others.
Data Exchange Standards
Data exchange is characterized as data import and data export.
The data exchange process is not typically reciprocal, but rather, users
import data purchased from data exporters (providers). These are usually
government agencies or commercial data sources. To be successful, GIS users
must know how to cope with the heterogeneous data environment. For data
export, each internal data model must be converted to a specific file structure
on disk or other media. The process is reversed for data import. The goal
of data exchange is to transfer information to enable understanding of
the phenomena being represented (Robinson, 1986).
There are three basic design strategies
that can be used by data exchange software:
Go to Section 2.4 - Image Compression
Alternatives and Media Storage Considerations
Back to Module 2 Main Page
References
Jensen, J. R., 1996, Introductory Digital Image Processing:
A remote sensing perspective, 2nd Edition. NJ: Prentice-Hall, pp. 60-61.
Robinson, A. H., J. Morrison, P. Muehrcke, A. Kimerling,
S. Guptill, 1995, Elements of Cartography, 6th Edition, John Wiley
& Sons, Inc., pp. 190-192.
