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Produced by the NASA Center for Aerospace Information (CASI)
E85 10096

An Investigation of Several Aspects of Landsat-5 Data Quali ^4151PI1

Robert C. Wrigley, Principal Irrvestigator

Quarterly Progress Report ^^' MqA ^^^

December 20, 1984 9

1,9^` N^, ^ya'4 Ci^V N1

ACP

Several Landsat-5 TM scenes were received during the repoifing

period: Parmer Countv. TX (31/36) of 6/8/84 as a P--tape; Shelby, MT

(39/26) of 7/18/84 as a GCP-corrected P-tape; San Francisco, CA

(44/34) of 5/2/84 as a GCP-corrected P-tape; White Sands, NM (33/37)

of 10/2 /84 as an unity RLUT A-tape and Great Salt Lake, UT (39/31) of

7/2/84 as a standard A-tape.:

Band-to-Band Registration

Quadrant 4 of the Parmer County, TX scene was tested for

band-to-band registration by the block correlation method. The

results are shown in Table 1. The results are very similar to our

earlier analyses of Landsat-5 TM data for the Corpus Christi and

Huntsville scenes. Within focal planes, all bands were very well

registered 1-u one another including the thermal band. Between the

primary and secondary focal planes, there was a mean misregistration

o'. 0.71+0.03 pixels in the across-scan direction and 0.19±0.03 pixels

ir, she along-scan direction. The Huntsville results were 0.66+_0.02

and 0.13±0.02 pixels, respectively. Although the 958 confidence

interva]z do not quite overlap between the two scenes, the results are

close c,,.-)ugh to be considered identical. An effort will be made to

determine when tht- software corrections were implemented to bring the

two focal planes into registration. When that date has been

determined, -re will test one or two s-enes processed after that date

to determine the effectiveness of the corrections. The dates of the

implementation should be generally available to the user community,

p^4 rticularly the TM AO investigators, so the users can avoid the early

data from both Landsat-4 and Landsat-5 if they wish to do so.

Table 2 is a summary of all the band-to-band registration results

we have accumulated to date. Only the mean misregistrations are

listed for each scene. Within a given satellite, the stability of

these results for a given band pair is of the order of a few

hundredths of a pixel for most band pairs. Table 2 shows the initial

misregistration between focal planes and the results of two apparently

different attempts to correct it (the Sacramento data of 8/12/83 and

the remake of the NE Arkansas scene of 8/22/82). Table 2 also shows

the initial problems with the thermal band and that they have long

since been corrected.

Geodetic Registration

The original concept for testing geodetic registration envisaged

testing P-tapes that had been fully corrected using grcund control

points (GCPs). In that case, T'ile geodetic location of a pixel was

(E85-10096 NASA -06-175531) IN INVES;IGAIION N85-23214

OF SEVERAL LSFEC7E CF LINrSil-5 EIT1 QUALITY

Quarterly Frogresf EeFort (krizcna Univ.,

Tucson.) 17 f HC lu g /bF 101 CSCL ^5B Unclas

G3/43 00v.96
supposed to be accurate within 0.5 pixels 90% of the time.

Unfortunately, GCP-corrected P-tapes have been rare and we have yet to

receive our requested GCP-corrected P-tai,: of the Sacramento scene of

2/1/83. In light of these facts, we decided to test the Scrounge

format tape of the same Sacramento scene which we had on hand. The

analysis would demonstrate the geodetic accuracy prior to the

GCP-correction and it could be compared to the GCP-corrected data when

we received it. Note that the Scrounge data was never intended to

meet the 0.5 pixel accuracy specification.

The test for geodetic accuracy was conducted by locating control

points in the image and on 7.5' quadrangle maps (1:24,000 scale),

estimating the image coordinates to the nearest half-pixel (14

meters), digitizing the map coordinate to the nearest 0.00001 degree

(1.1 meters), using the digitized map coordinate in a program provide

by EROS Data Center to predict the image coordinate of the point, and

comparing the observed image coordinate with the predicted coordinate.

June Thormodsgard of EROS provided the program to predict the

coordinates from the information in the HAAT file of a Scrounge tape

(i.e. the WRS center, WRS offset, the projection and the rotation

angle). The control points were selected after consultation with the

Geometronics Branch of the Geological Survey in order to select points

with the best possible location accuracy on 7.5' quadrangles.

The results for the comparison for fourteen control points taken

throughout the scene are shown in Table 3. The line/sample

coordinates for the control points as interpreted from the image using

an interactive display system are listed under Image Location. The

coordinates derived by the EROS geolocation program from the digitized

map points are listed under Predicted Location and the differences

between the two are listed under Error. In general, the

correspondence is far better than expected for system-corrected data.

The mean errors and standard deviations for these fourteen points are

0.0±1.2 lines and -9.7±1.7 samples. (Our workshop report that the

line direction error was 4.0+1.2 was incorrect because the image file

header record had been treated as four image lines and those lines

should have been subtracted from the image line coordinates.) Note

that the standard deviations are of the order of 1.5 pixels or three

times the allowable error for geodetic registration. Although the

population is small (14 points) these standard deviations are probably

a good estimate of those for a much larger population. If so, these

standard deviations indicate that the prPsent technique will not be

adequate to test geodetic accuracy to 0.5 pixels. We are pursuing

improvements with the Geometronics Branch at the Geological Survey as

mentioned in the previous report.

Interdetector Noise

The goal of the interdetector noise task is to characterize the

differences in response between detectors in a TM band. This include:

Fourier analysis to determine the periodic noise in individual

detectors on A tave data. Previously, we examined nearly uniforr

areas over water bodies in two Landsat-4 scenes: Washington D.0 or

11/2/82 and San Franscisco on 12/31/82. Periodic noise was present it

TM1-4 in both scenes. A noise component at a spatial frequency of
0.31 cycles per pixel (32 KHz in the time domain) was particularly

prominent. We also explored the relationship between varying amounts

of noise in individual detectors and low level striping due to the

histogram normalization used in A-tape production. Similar analysis

of Landsat 5 data is being performed.

Two 256x256 pixel windows over the Great Salt Lake in quadrant 4

of the 7/2/84 scene were examined recently. One window was in a dark

water area and the other in water with medium grey levels. The

f.orescans and backscans were copied into separate files before

analysis because other Landsat Data Quality investigators had shown

that some artifacts of TM imagery were dependent on scan direction.

Means, standard deviations and power spectra for each detector in each

direction were computed.

Periodic noise was detected in all hands of Landsat-5 except TM6,

where the low sampling rate of the sensors would obscure the noise at

the frequencies observed in the other. bands. Nois, at .087 and .174

(a harmonic of .087) cycles per sample was detected in TM1-TM5 and

TM7. (In Landsat-4, TM bands 5 and 7 were free of periodic noise.)

Noise was particulary strong in TM5, with root sum square (RSS)

peak-to-peak values in the frequencies .0859, .0898, .1718, and .1757

cycles per sample (cps) ranging from 0.54 in detector 1 to 3.26 in

detector 7. Table 4 shows the results for these frequencies for the

dark water area. Noise at .05 cps, .21 cps, and .42 cps (a harmonic

of .21 cps) was observed in TM1-4, but not in TM5 or TM7.

Analysis of of the Salt Lake scene windows will be completed to

quantify the noise content in all detectors and determine its

consistancy within the scene. Spectral analysis of so...e small areas

on the B-tape of an October 1984 White Sands scene will be performed

to detemine the consistency of periodic noise in Landsat-5 scenes.

The grey level means of each of the two water areas in the Great

Salt Lake were calculated in order to determine any dependence on scan

direction or on individual detectors. Separate means were calculated

for each detector in each band for both scan directions. The results

are shown for the dark water area in Tables 5 and 6. To examine any

scan direction effect, the differences between the forescan and

backscan means were calculated for each detector. The m,an difference

for each band is shown in Table 6 together with the standard deviation

of the sixteen differences (four for TM6). Table 6 shows that the

forescan means were approximately one and one half grey levels higher

than the backscan means in TM1-4 in the dark water area. The

differences between forescan and backscan means in TM5,7 were less

than 0.1 grey level.. The differences were approximately one grey

lei;^1 in the medium water area for TM1-4 and again less than 0.1 for

T115,7. In the January workshop, we had reported differences between

TM5 forescan and backscan means of about three grey levels. These

apparent differences were due to an error in calculation on a forescan

data set. Tables 5 and 6 show the corrected TM5 means. Since the

Great Salt Lake is east of the Great Salt Desert, the differences

beween scan directions were probably due to the bright target

saturation effect noted by other Landsat Data Quality investigators.

Detectors in the primary focal plane have been observed to have

i _
elevated responses after saturation or near saturation (grey levels

above.2 200). The dark water area, in particular, was east of such an

area but the medium water area was affected only minimally. The

magnitude of the saturation effect on the Salt Lake data may have been

exaggerated for two reasons: round-off in quantizing the sensor data

to 255 levels, and an uncorrected offset of about 50 pixels between

the location of the forescans and backscans.

Tables 5 and 6 could also he used to examine effects due to

individual detectors within a scan (i.e. residual striping).

Different patterns were present in different bands. TM1 and TM3

exhibited an odd detector/even detector oscillation about their means

with an amplitude of 0.3-0.5 grey levels. TM4, TM5 and TM7 had more

complex, but still regular patterns. The maximum difference between

detector means was found in TM3 and was 1.7 grey levels. These

differences, although small, may be statistically significant, but the

effects due to auto-correlation will have to be considered before any

statement on significance can he made.

Modulation Transfer Function

The MTF analysis of the Thematic Mapper on Landsat-4 was

completed by Schowengerdt during this period. Results of the San

Mateo Bridge MTF analysis of two dates (12/31/82 and 8/12/83) were

previously reported and showed the effective IFOVs (EIFOVs) were 40.8

and 48.6 meters, respectively. For the August 12, 1983 s.,ene a

near-simultaneous underflight occurred with a multispectral aircraft

scanner covering TM bands 1-4 at 7 meter resolution. Selected areas

of TM and aircraft scanner data near San Jose and Stockton, California

were registered, matched for radiometry, and Fourier transformed. The

ratio of the Fourier transforms yielded the complex transfer function

whose modulus was the MTF. After correction for the magnification of

the TM image and several smoothing steps (spectrally, 3x3 filtering in

the Fourier domain, azimuthally in the Fourier domain by 30 degree

sectors, and least squares polynomial fitting), the MTFs were obtained

for both areas.

The MTFs from the two-image analysis were quite consistent for

the two study areas and with the MTF derived from the bridge analy-sis

in the same scene although the latter was somewhat lower. EIFOVs

derived from the two-image analysis were 40.4 meters along-scan and

42.4 meters across-scan for the San Jose area and 38.7 meters

along-scan and 46.0 meters across-scan for the Stockton area.

Schowengerdt suggested that all these values for the EIFOV are higher

than those developed by Brian Markham of Godard from a system model

because that model did not account for sampling the original. signal

into 30 meter pixels. Schowengerdt's Progress Report covering the

period and showing the MTF plots is attached to and made part of this

report.

The White Sands resolution target of sixteen 15 meter, black,

oiled squares was laid down successfully in late September 1984. By

the time of the first TM acquisition on October 28, parts of the

target had been covered by sand due to unusual winds and rainfall. A

35 mm photograph taken from a helicopter at 5000' on the same day
g

should be useful in correcting for these problems when processing the

TM data for MTF. An A-tape with unity RLUTs has been received for the

scene.

TABLE 1

Summary statistics for band-to-band registration of

Thematic Mapper band combinations for Quadrant 4 of

the Parmer Co., TX scene of June 8, 1984 in TIPS

rormat. All correlation blocks with the correlation

coefficient <0.6 were discarded (<0.3 for bands 6 vs

7). The unit of misregistration (shift) is pixels.

TM Shift Number Mean Std. 95% Confidence

Bands Direction of Shift Dev. Interval for

31ocks Mean Shift

3 v; 1 Across-scan 182 -.03 .07 -.04 to -.02

Along-scan 182 .00 .07 -.01 to .01

3 vs 2 Across-scan 196 -.04 .05 -.04 to -.03

Along-scan 196 -.01 .04 -.01 to .01

3 vs 4 Across-scan 150 -.01 .11 -.02 to .00

Along-scan 150 -.01 .13 -.04 to .01

3 vs 5 Across-scan 188 -.71 .16 -.73 to -.69

Along-scan 1.88 .21 .14 .19 to .23

3 vs 7 Across-scan 174 -.72 .15 -.74 to -.69

Along-scan 174 .17 .12 .16 to .19

5 vs 7 Across-scan 193 -.01 .06 -.01 to .00

Along-scan 193 -.03 .08 -.05 to -.02

6 vs 7 Across-scan 126 -.05 1.25 -.27 to .17

Along-scan 126 -.42 1.18 -.63 to -.21
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Spatial Frequency, cycles/sample

.0859 .0898 .1718 .1757 RSS

.45 .29

----------------------------------

.21 .24 .62

.61 .40 .38 .66 1.06

.45 .26 .16 .26 .60

.85 .42 .35 .56 1.15

.71 .45 .27 .38 .97

.59 .33 .21 .29 .76

.41 .29 .20 .40 .67

.84 .53 .15 .42 1.09

.55 .33 .20 .32 .75

2.65 1.52 .44 1.06 3.26

.52 .34 .23 .35 .75

.85 .55 .31 .57 1.20

.61 .40 .27 .51 .93

1.04 .57 .32 .34 1.27

.56 .33 .22 .28 .75

.38 .25 .16 .24 .54

Control Point

TABLE 3

GEODETIC REGISTRATION TEST

Sacramento, CA (44/33), February 1, 1983

System Corrected Scroun g e Format

Image Location(L/S) Predicted Location(L/S) Error(L/-

1. Clarksville

2. Rocklin-A

3. Rocklin-B

4. Elk Creek

5. Shippee

6. Valley Ford

7. Linden

8. Galt

9. Kenwood

10. Detert

11. Sutter Buttes

12. Maxwell

13. Princeton

14. Lake Combie

3624.0/5531.0

2926.0/5229.0

3165.0/5042.0

792.0/ 633.0

247.0/3170.5

5755.5/ 193.0

5836.0/6272.9

4830.0/5037.0

5198.0/1235.0

4089.5/1242.0

2095.0/3029.0

1524.0/1800.0

1154.0/2087.0

2189.0/5431.0

3623.4/5540.6

2923.7/5238.5

3168.1/5056.6

791.8/ 642.6

246.3/3181.1

5757.9/ 200.8

5835.2/6281.9

4831.3/5047.4

5199.2/1244.5

4089.2/1256.6

2095.7/3038.6

1523.3/1808.7

1154.4/2095.3

2188.0/5439.8

0.6/ -9.

2.3/ -9.

-3.1/-14.-

0.2/ -9.>

0.7/-10.

-2.4/ -7..

0.8/ -9

-1.3/-10.

-1.2/ -9.

0.3/-14.;

-0.7/ -9.:

0.7/ -8."

-0.4/ -8.

1.0/ -8.

Mean Error(L/S): 0.0+11-.2/-9.7+1.7

TABLE 4

Periodic Noise Components in Thematic Mapper Band 5

Peak-to-Peak Values at Discrete Spatial Frequencies for

Dark Water Area Forescans in Great Salt Lake on July 2, 1984
TABLE 5

Grey Level Means by Detector for

Salt Lake Dark Water Forescans

Detector TM1 TM2 TM3 TM4 TM5 TM6 TM7

16 70.8 26.8 16.9 11.5 4.5 137.4 5.0

15 69.6 26.8 16.3 11.3 4.7 go 5.1

14 70.3 27.0 16.8 11.6 4.5 of 4.6

13 69.5 27.0 16.6 11.3 4.7 It 4.6

12 70.5 26.5 16.8 11.4 5.2 137.4 4.7

11 69.6 26.2 16.1 11.3 4.3 of 4.3

10 70.5 27.1 16.6 11.2 4.4 it 4.5

9 69.9 26.9 15.9 11.3 4.3 If 4.6

8 70.5 26.4 16.6 11.6 4.6 137.4 4.5

7 69.4 26.9 16.2 11.0 4.6 if 4.2

6 70.6 26.4 16.7 11.3 5.3 It 4.5

5 69.7 26.9 15.7 il.0 5.1 If 4.3

4 70.4 27.2 16.8 11.2 4.8 137.2 4.4

3 69.9 26.8 15.9 11.3 4.8 If 4.4

2 70.7 27.1 17.0 11.3 4.5 of 4.9

1 70.0 26.7 16.3 ll.0 4.6 Of 4.9

Band Mean 70.1 26.8 16.4 11.3 4.7 137.4 4.6

TABLE 6

Grey Level Means by Detector for

Salt Lake Dark Water Backscans

Detector TM1 TM2 TM3 TM4 TM5 TM6 TM7

16 69.7 25.4 15.7 9.8 4.6 137.8 5.0

1a 68.4 24.9 14.4 9.6 4.7 5.2

14 69.2 25.7 15.6 9.7 4.6 of 4.6

13 68.3 25.0 14.6 9.6 4.7 It 4.7

12 69.5 25.0 15.5 9.7 5.2 137.8 4.8

11 68.4 25.0 14.3 9.9 4.4 4.4

10 69.5 25.5 15.5 9.9 4.5 It

9 69.0 25.2 14.4 9.7 4.4 of 4.7

8 69.3 25.2 15.9 9.8 4.7 138.0 4.6

7 68.3 25.5 14.2 8.9 4.7 4.3

6 69.3 25.1 15.4 9.9 5.3 4.6

5 68.6 25.5 14.4 9.7 5.2 to 4.3

4 69.3 25.6 15.5 9.7 4.9 137.8 4.5

3 68.7 25.0 14.6 9.9 4.9 It 4.5

2 69.2 24.9 15.7 9. 4.5 of 4.9

1 68.2 25.3 15.0 9.3 4.7 01 4.9

Band Mean 68.9 25.3 15.0 9.7 4.8 137.8 4.6

Mean Difference 1.2 1.5 1.4 1.6 -0.06 -0.5 -0.0;

Standard Deviation 0.2 0.3 0.4 0.2 0.04 0.2 0.0:1
LANDSAT-4 AND -5 THEMATIC MAPPER

MODULATION TRANSFER FUNCTION (MTF) EVALUATION

Progress Report

September 15. 1?84 - December 15, 1?24

submitted to:

Robert C. Wriglex

NASA Ames Research Center

Moffett Field, California

Robert Schowengerdt. Principal Investigator

Arizona Remote Sensing Center

Office of Aric Lands Studies

U. of Arizona

Tucson. AZ c3'21

Januar>• 23, 1 X85
Introduction and Summary

During this contract period, we ha ,.,e completed the MTF

anal y sis for the Landsat-4 TM. This analysis involved the

San Mateo Bridge as a special target in two scenes, 12:31/81

and 8/12/83, of the San Francisco region. We also performed

a two-image corlparison of TM and high resolution aerial

Daedalus scanner imagery taken on the morning of the 8/12/83

scene. The results from these anal y ses are consistent and

appear to be repeatable, leading to a high degree of

confidence in the MTFs obtained,

Also during this contract period, i..le successfully

constructed an oil-on-sand target on the White Sands Missile

Range in New Mexico for MTF studies of the Landsat-5 TM.

Vithin six weeks of the target's construction, however. it

had been degraded b y continuing rainfall and wind at the

site. A Lanosa'.-5 image of the target was obtained on

October 28, 1984, and a 35mm photograph of the target from a

helicopter at 5,000 feet altitude on the same day will by

used to calibrate the changes in the target since initial

construction. Re-oiling of tht> target is planned for the

first quarter of 1985.

San Mateo Brid g e Analysis.

The results of the San Mateo Bridge MTF anal y sis w,*ts

reported in the progress report of August 14, 1964. For

cc , nvenience the final EIFOVs obtained are repeated here in

Ta.bl e 1 .

TABLE 1

SAN MATEO BRIDGE MTF ANALYSIS

TM EIFOV(m)

date

TM band 12/31/872 8/12/83

1 - 49.8

2 - 50.9

3 313.6 48.1

4 40.8 45.4

5 41.9 46.9

6 - -

7 40.0 44.5
Bands 1 and 2 from the 12/31,'82 date were of such low

contrast that reliable MTF data could not be obtained. This

problem of low contrast, and consequentl y low signalto-noise, for the shorter wavelen g th bands is also probably

influencing the EIFOV for band 3. The inconsistently 10•>>

value in band 3 is therefore ionored in further comparisons

with the two-image anal y sis results. Likewise, the image of

the bridqe in TM band 6 (thermal) has negligible contrast

because of the 1-Om IFOV in that band.

Two - image Analysis

The final procedures for comparison of TM and high

resolution aerial scanner imager y were described in earlier

progress reports. The steps in the analysis are summarized

in Fiqure 1:

FIGURE 1

TWO-IMAGE #4NALYSIS PROCEDURE

1. Register TM and high resolution imagery

This is accomplished by visual location of

control points in the two images, followed by

a least-squares power series polynomial fit

to the control points to obtain the warping

function. In this case, 50 control points

were cbtained, and a quartic polynomial was

used. This high order was required to match

high frequenc y line "wiggles" in the aerial

scanner imagery.

2. Match TM and high resolution imager y radiometry

This was accomplished b y calculating the twodimensional scattergram between the registered images. A linear leas t.-squares fit to

the scattergram was then done. y ielding the

linear g ra y level transformation to be

applied to the high resolution imager y to

make its mean and var ante equal to those of

the TP1 imager y . This step is important in

minimizing FFT border effects in later steps.

3. Mask common area a.7d fill border

The same ground area was masked in both sets

of imager y and the surrounding border region

filled with the image moan value within the

masked region. This step is important in

minimizing FFT border effects. in conjunction

with Step 2.
4. Ratio F-T of two 512 512 imaoes

The geometricalli and radiometrically registered pair of images may be considered an

object-image pair, with the TM image being

the ricult of spatial filtering, b y the 'rM

MTF, of the high resolution (object) image.

BY linear filtering theor y . therefore, the

ratio of their Fourier transforms y ield the

complex transfer function, whose modulus is

the MTF.

5. Correct for 4x magnification of TM image

In the registration process, the TM ;mage was

first ma g nified by a factor of four with bilinear

resarnpling to permit convenient visual

control point selection and comparison

with the high resolution imagery. Tnis

res amp Iing acts as a filt,_r on the the TM

image that must be corrected for. Empirical

calibration of the filte.- wa= done b y comparing Fourier transforms of the TM image

before and after magnification.

e. Smooth the MTF

the result of the ratio in Step 4 is quite

noisy from frequenc y -to-frequenc y and smoothing i5. necessar y in order to obtain reliable

results. Several smoothing steps were used:

Average the complex transfer function 04

the bands 1-4 in the primary focal

p 1 ane

3 X 3 median filtering of the complex

transfer function

Azimuthal averaging of the complex

transfer function in 30 degree sects -s

Least-squares polynomial fitting oT the

azimuthally-averacied MTF

A comparison of the final MTFs obtaineo from two

di fferen t areas ;n the 8/11`83 scene is shown in Figure 2.

This profile is along the same frequenc y direction as

measured b y the the bridg e analysis. Fioure 2 indicates

that the two-image technique is quite repeatable between

these two image areas.

In Figure 3, the MTF derived from the two-image

anal y sis is compared to that resulting from the bridge

analrais for the same scene. It is clear that the two

independent techniques are yielding comparable results.
Fir,aII y , in Figure 4, a comparison is mada between

tnese image-derived MTFs and s y stem model MTFs obtained by

Markham (NASA Technical Memorandum 36130), The :magederived MTFs are considerably lower than the s y stem model

MTFs because the system model did not attempt to include the

effects of sampling, resampliog (the TM data analyzed are

P-data corrected for s y stematic geometric distortions), and

atmospheric scatterin g . All of these are factors in the

final image-derived MTF, however. A SUMMAr y comparison of

EIFOVs derived using various techniques is uiven in Table 2:

TABLE 2

E I F OV b,'MMARY

TM4 BANDS 1-4 AVERAGE CIFOV(m)

technique

San Mateo Bridge

San Jose Two-imac,e

Stockton Two-image

Sy stem Model (Markham)

date EIFOV (m)

1 2/ 31/82 40.8 ( TM4 only)

8/12/83 48.6

13/12/83 40.9/42.4 (sc an/ traclt)

9/1 c183 38.7/46.0

'05.9/3Z.1

White Sands Target

In late Sep territ a r , 1984, surve y ing and construction of

the target shown in Figure 5 were performed at White Sands.

The target is created b y spra y ing road oil on the sand in

the prescribed pattern. The target is desi g ned 'Co samplo

the TM pixel grid (and consequently its noint spread

f;inction) b y a subpixel increment of 0.25 and thereb y avoid

aliasing in the measurement.

B y the time of the first successfui TM acquistion,

10/28/84, the target had been degraded ano partia!ly covered

b y sand because of unusuall y heav y rainfall and winds at the

test site. However•, the condition of the tar g et was

recorded in a 35mm photograph taken from a helicopter at

5000 feet altitude on the da y of the satellite ovcrpaas.

We have received the TM imane in raw, unprocessed form and

plan to digitize the 35mrr, target image for use in analysis

of the TM image.
co

O

S

O

FIGURE 2.

^r

COMPARISON OF TWO-IMAGE ANALYSIS FOR TWO AREAS

N

O

O O10 0,1 0.2 0,3 0,4 0,5 0,0

SPATIAL FREQUENCY (V:C`(CLE/PIXEL)
FIGURE 3.

COMPARISON OF BRIDGE AND TWO-IMAGE ANALYSES

N

00

C

' • TvgO- IMAGE ANALYSIS

•• SAN JOSE STUDY AREA

^- BRIDGE ANALYSIS ' • .

o '-

0 1

c

0, 0 0,1 0, 2 0, 3 U, 4 0, 5 0.6

SPATIAL FREQUENCY (V;CYCLE/PIXEL)
f

r.

HURL 4.

COMPARISON BETWEEN IMAGE-DERIVED AND SYSTEM MODEL MTFs

N

r-^I

co -•^

SYSTEM MODEL (MARKHAM)

2:7

^. '•.1 TRAC K

TWO-IMAGE ANALYSIS ••.^

c SAN JOSE STUDY AREA_ SCAN

TRAC `.^ SCAN

0

°0,0 0,1 0,2 0,3 0,4 0,5

SPATIAL FREQUENCY M CYCLE/PIXEL)

0,6
FIGURE 5. ORIGNVAL PACE tS'

OF POOR QUALITY

x

x

IM WHITE SANDS TARGET - 10/84

• EACH BLACK SQUARE IS 15 x 15m

• CENTER-TO-CENTER DISTANCE IS 157,5m (5,25 PIXELS)

x

x

1\ tXAMPLE 30 X 30m PIXEL GRID