ding 
ions 
eing 
ition 
with 
jally 
the 
and 
din 
tion 
sing 
acts 
ere 
and 
ring 
ited 
lute 
256. 
hen 
nof 
gle 
nto 
rely 
ns, 
ose 
ted, 
tion 
ing 
will 
ISOr 
tion 
nity 
the 
  
67 
As an adjunct to this equalization process, new processing techniques involving the use of dark shutter information were 
investigated for their potential to minimize remaining image artifacts. One technique based upon characteristics of the DC 
restore function and short term time variations in detector response was proposed as the most effective candidate. 
In order to test the hypotheses of whether such equalization techniques would prove effective in removing streaking and 
striping, it was decided that, since no data is yet available from the ETM+, some simulated version of the calibrator panel 
equalization would be used to calculate correction coefficients which could be applied to real TM reflective band imagery. This 
simulation was created by locating an extremely uniform region within a Landsat 5 TM image, assuming that it was perfectly 
uniform, calculating the correction coefficients, applying them to the entire image from which the extraction was made, and to 
other images, both of the same scene as well as others collected at different times, and evaluating the results both 
quantitatively and qualitatively. A similar procedure was investigated as an alternative to using pre-launch measured detector 
gains for Landsat 4 (Fischel, 1984). The details of the process follow. 
2. CHARACTERIZATION OF THEMATIC MAPPER RESPONSE 
At the end of every scan of the TM, a shutter passes in front of the focal plane. The shutter provides both a dark source 
(blocking light from the aperture) and a light source for reflective band calibration. The light intensity is varied by turningon and 
off, in different combinations, three different calibration lamps providing seven different light levels. Each level is maintained 
for approximately 40 scans. Therefore, when provided radiance estimates for the light levels, eight different calibration points 
are available for establishing an estimate of each detector's response curve. Since the detectors are assumed to be linear, a 
linear least squares curve fit is calculated for all of the points providing a gain and bias value for each detector. 
Inthe ETM+ the configuration is very similar, except that only one lamp will be used, thus providing a single light intensity level 
instead of seven non-zero levels. 
3. ESTABLISHMENT OF A UNIFORM EQUALIZATION TARGET 
Creation of an equalization target required two steps. First, a Level 0 (raw, uncalibrated detector outputs) image of a known 
relatively uniform scene was selected. In this case it was fortunate that Santa Barbara Research Center, the developer of the 
TM, was kind enough to lend us images of the Libyan desert collected by Landsat 5 from 1984 to 1991, which they had used for 
detector response drift studies in recent years. The August 27, 1991 image was selected as the source for equalization. 
Second, an automated search of the image from spectral band 1 was conducted to find the most uniform area withinthe scene. 
A sliding window, 512 by 512 pixels in size, was placed over the image, beginning in the upper left hand corner. The standard 
deviation of the pixels within the window was calculated and stored with the window location. The window was then repeatedly 
shifted maintaining a 64 pixel overlap with the previous window, and the accompanying standard deviation calculated for each 
area until the entire image had been covered. That window of pixels with the smallest standard deviation was assumed to be 
the most uniform area within the scene. Inthe case ofthis image, this was in the location starting at sample 449 and line 2049 
(lines are designated as running in the cross track direction). Statistics for this region were: 
[12115.1 DN 
-2.51 DN 
Min=104 DN 
Max=149 DN 
The standard deviation was actually small enough to be comparable to the estimated system noise level. 
4. EXTERNAL EQUALIZATION PROCESSING 
The average Entrance Aperture Radiance (EAR) values were calculated from the uniform source image as follows: 
For each reflective band, m, and each detector, k: 
i=1 j=1 
hn T (nscan) (nsamp) (1) 
nscan NSaMP (ea, source, ;-bias; ;) 
Ee 
  
IAPRS, Vol. 30, Part 5W1, ISPRS Intercommission Workshop “From Pixels to Sequences’, Zurich, March 22-24 1995