linear features in wairarapa: quantitative study using landsat imagery
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Linear features in Wairarapa:Quantitative study using LandsatimageryS. E. Belliss a , A. D. W. Fowler a & M. J. McDonnell aa Department of Scientific and Industrial Research , RemoteSensing Section Physics and Engineering Laboratory , PrivateBag, Lower Hutt , New ZealandPublished online: 28 May 2012.
To cite this article: S. E. Belliss , A. D. W. Fowler & M. J. McDonnell (1985) Linear featuresin Wairarapa: Quantitative study using Landsat imagery, New Zealand Journal of Geology andGeophysics, 28:2, 359-367, DOI: 10.1080/00288306.1985.10422233
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New Zealand Journal of Geology and Geophysics, 1985, Vol. 28: 359-3670028-8306/85/2802-0359$2.50/0 © Crown copyright 1985
Linear features in Wairarapa:Quantitative study using Landsat imagery
359
S. E. BELLISSA. D. W. FOWLERM. J. McDONNELLRemote Sensing SectionPhysics and Engineering LaboratoryDepartment of Scientific and Industrial ResearchPrivate BagLower Hutt, New Zealand
Abstract An analysis of linear features mappedfrom a Landsat image of a geologically and topographically varied area of Wairarapa showed that50% of them could be readily located in a subsequent ground survey. Most were surface expressionof faults; some were escarpments; some were particularly straight valleys that may have some(unrecognised) structural control; and a few wereroads and vegetation changes. Where those associated with ground features were running at rightangles to the image sun direction, they wereenhanced by shadowing. Such shadowing was alsoresponsible for most of the artifacts for which noground feature could be identified.
A comparison of different image enhancementoptions indicates that a band 4 image (MSS band7), filtered and then stretched, was best for studyinglinear features.
Keywords linear features; lineaments; faults;satellite methods; remote sensing; imagery; Landsat; Wairarapa; structural maps
INTRODUCTION
Wairarapa comprises three distinct topographicregions. A central lowland of late Tertiary andQuaternary sediments is bounded to the west byuplifted Mesozoic greywackes and argillites whichform the Rimutaka and Tararua Ranges (up to 1500m). To the east, coastal ranges composed predominantly of Mesozoic siltstone and sandstone seldom exceed 610 m. North of Masterton, the onlysignificant urban centre in the area, the central lowlands give way to rolling hill country. In the southeast, the coastal ranges become the rugged AorangiRanges (up to 1100 m).
Received 4 November 1983, accepted 10 August 1984
Many parallel and subparallel faults with a predominant northeast direction traverse Wairarapa.Some are still active, especiallythose separating theRimutaka and Tararua Ranges from the centrallowlands and those around, and north of,Masterton.
The central lowland area ofWairarapa is mainlyin pasture but horticultural blocks are commonaround the small towns. The eastern coastal rangelands are farmed; much of the steeper terrain isscrub or bush covered, or planted out in exoticconifers. On the Rimutaka, Tararua, and AorangiRanges, native forest predominates.
Because of this variation in land use and topography, and because of the large number of mappedfaults, Wairarapa was chosen to study the use ofsatellite imagery for mapping linear features.
A linear feature may be defined as any line oralignments offeatures seen on the images, and mayinclude fracture systems, faults, escarpments, anddrainage alignments. It is at ground survey stagethat one can distinguish structural lineaments fromlinear features due to other causes (e.g., roads, railways, cadastral boundaries, shelter belts, artifactsof sun angle).
Any literature search of geological remote sensing will reveal a multiplicity oflinear feature studies ranging from small-scale ones (i.e. hundreds ofmetres) (e.g. Norman 1969) through average (e.g.,Cardamone et. a1. 1976;Csillag 1982) to enormous(i.e. continental scale) (e.g., Ostaficzuk 1981). Thisstudy attempts to answer four questions:(1) What proportion of the linear features on sat
ellite imagery are structural lineaments?(2) What proportion of the major mapped faults
(evident on the ground) are visible on satelliteimagery?
(3) How subjective is such a linear feature study?(4) What is the best image product for mapping
linear features?Although a similar study was undertaken of a
Landsat band 4 image of an area in south centralTennessee (Moore & Waltz 1983) and an imageprocessing pathway to produce directionallyenhanced images described, no field checks weremade to determine the nature of the linear featuresso produced.
Linear features were mapped in Wairarapa eastof the Wellington Fault and south of Mauriceville,that is, NZMS 260, sheets T25 C D, U25 C, pt S26,
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360 New Zealand Journal of Geology and Geophysics, 1985, Vol. 28
Fig.l Linear features in the Wairarapa area identified from Landsat. This is a band 4 image which has been highpass filtered, then stretched. It proved to be the best enhancement option for a linear feature study of this scene.
T26, U26, pt R27, S27, T27, R28, S28, and T28(l :50 000 scale) (Fig. l).
The Physics and Engineering Laboratory, DSIR,has several images of Wairarapa, all of which arepartly cloud covered. PEL I, (Scene 2334-21132)was taken on 22 December 1975 with an 80 m
resolution and four spectral bands 1-4 (Multispectral scanner (MSS) bands 4-7; these band widthsare 500-600, 600-700, 700-800, and 800-1100 nmrespectively). This is one of the better images, beingrelatively clear, but with patches of cloud over theeastern rangelands (see Fig. 1). In it, the sun has
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Belliss et al.-Linear features, Wairarapa
an elevation of 48° and an azimuth of 78°. As the0111y two other relatively cloud free images havevery similar sun angles, and as the enhancementprograms take time to set up and run, it was decidedto restrict this study to a single image (PEL 1).Images referred to in this paper have been processed and written using the PEL image processingsystem (McDonnell & Pairman 1982; McDonnellet al. 1983).
The only large-scale geological map of Wairarapa is NZGS 1:250000, sheet 12-Wellington(Kingma 1967). Linear features identified on thesatellite image were checked against the faultsmapped on this sheet. Other geological maps usedwere Tinui-Awatoitoi, Nl59 and Pt N158 (1:63 360series) (Johnston 1975), maps of the northern Aorangi Range (Bates 1967), and current 1:12 500 fieldand provisional compilation sheets ofT25 CD, T26AB (Francis in prep.).
METHODS
Linear feature mappingA standard colour composite and a standard blackand white band 4 (MSS band 7) image of PEL Iwere printed at 1:250 000. Linear features exceptobvious roads or railway lines were traced ontoacetate overlays.
All linear features longer than 0.5 cm (~2 km)were plotted onto rose diagrams in 10° groups. Allmeasurements are to grid north. The fault linesmarked on the geological map were similarly plotted. Because the individual faults tend to be continuous over long distances, and may vary in strike,a measurement was taken each time any fault lineoccurred within a square made by the lines of latitude and longitude marked on the geological map(i.e. approximately 9 X 9 km squares). Thus, thenumbers of measurements taken on the faults wererendered commensurate with both the numbers of,and scale of, linear features plotted on the satelliteimages. After these were compared, differentenhancements were undertaken to make the Landsat images more equivalent to the geological map.These were compared again to the geological mapand other available geological maps, and tested bythe two field checks.
Image enhancementA variety of image enhancement options wereapplied to the band 4 image (800-1100 nm). Thisnear-infrared band picks up water very well, thusshowing up river systems and moist areas betterthan the other three bands. Also, bare rock, soil,and vegetation all have a relatively uniform greytone on band 4 images. This decreases tonal con-
361
trasts at land-cover boundaries. In addition,atmospheric haze penetration is better in this partof the electromagnetic spectrum. It is for these reasons that this band is usually the best for geologicalstudies. Once the best enhancements were chosen,colour images using bands I, 2 and 4 were similarlyproduced (see Appendix 1).
A set of filtered images was made to decide whichenhancements to use. Once the best one was determined, it was enhanced by a further set of options;from these, the best was selected, and so on.
The images tested were:1. Bands 1, 2, 4 (standard colour composite).2. Band 4, histogram equalised.3. Band 4, 7 X 7 HPF, XADB* = 1, stretched.4. Band 4, 7 X 7 HPF, XADB = 1, histogram
equalised.5. Band 4, 7 X 7 HPF, XADB = 2, stretched.6. Band 4, 15 X 15 HPF, XADB = 4, stretched.7. Bands 1,2,4, 7 X 7 HPF, histogram equalised
XADB = 2.8. Bands 1,2,4 DHP? 7 X 7 histogram equalised.9. Bands 1,2,4, 7 X 7 HPF, histogram equalised
for TL 1, 501, BR 1000 1400t.10. Bands 1, 2, 4/sum ratio histogram equalised.
After Landsat linear features were checked againstthe geological maps and the best image product wasselected, a linear feature overlay was plotted fromthis by another operator. This was used to test thesubjectivity of linear feature identification.
RESULTS
The rose diagrams (Fig. 2A, B) show a disparitybetween Kingma's (1967) geological map fault orientations and linear features drawn from a standard Landsat image. The major trend in both is 155SO, but the Landsat image also has a secondarytrend at 315-345°. This trend is also present inKingma's fault orientations but is very minor.
Much of this disparity between the map and theimage is due to sun angle. Landsat passes over NewZealand at approximately 0930 h (New ZealandStandard Time), and in consequence, the sun wasshining down the line of the major known .faultsin the area. Thus, they do not show up to best effect.Of course, any topographic features at right anglesto the sun angle have been enhanced by shadowing.
*HPF = high pass filter; XADB = add back factor; DHPF= direct high pass filter.
[The full PEL I scene includes a large expanse of sea inthe south and east. These areas were excluded from thehistogram equalisation program. These figures are givingthe top left and bottom right pixel numbers of the subscene that was used.
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362 New Zealand Journal of Geology and Geophysics, 1985, Vol. 28
Fig. 2 Directional trends of thelinear features on the geologicalmap, a standard band 4 Landsatimage, and three differentenhancements of a band 4 Landsat image of Wairarapa.
Be-Fault orientationsfromKing ma (1967)
D-Same as CSEB linear feature plot
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C-Band 4wi!h 7X7High Pass Filter, add backfactor of 1, and stretchedAUWF linearleature plot
E-Band 4 with 15X15High Pass Filter, add backfactor of 1,and stretched.
F-Band 4 with 15 x15High Pass Filter, add backfactor of 4, and stretched.
In the filtered images (Fig. 2C-F), the secondarytrend (at 315-345"), although present, is not quiteso strong. An exception to this is the image thatwas enhanced with a 15 X 15 high pass filter andan add back factor of 4 (F in Fig. 2) (see Appendix1). This produced an image with very high contrast, enhancing the effectofthe shadowing as muchas it increased the depiction of the more subtle linear features. The weakening of the secondary trendin the filtered images is due to one or more of thefollowing:1. There is less real structure to show up.2. Having already done the first comparison of
the geological map to Landsat, the operatorsare employing their own (mental) filtering tothe data.
3. Structures trending in this direction may beolder than the northeast-southwest structures,and thus their topographic ewression is weaker.
4. Structures trending in this direction may be thesame age as the northeast-southwest structures, but secondary.
That this secondary trend persists in all theenhancement options tested suggests that at leastsome of these linear features are structural lineaments. The possibility of structures at approximately 90° to the major structural trend inWairarapa should be born in mind in future fieldinvestigations of this area.
In addition to the comparison ofLandsat-mappedlinear features to those on the geological map, anattempt was made to determine if any new struc-
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Belliss et al.-Linear features, Wairarapa 363
Fig. 3 Ground truth surveyresults of the linear features ~mapped around MauricevilleNorth. The linear features atmiddle left marked 'C' were not Nvisited but are a series of ridge Icrests.Ofthe linear features drawnhere, 56% have been identified;25% of the linear features markfault traces. Unnumbered linea-ments were not identified. I F
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I Branch of the Carterton Fault. 2 Probable branch of the Masterton Fault. 3 Limestone escarpment (not faultcontrolled). 4 Alfredton Fault and its southern extension. 4a Branch of the Alfredton Fault. 5 Limestone escarpment. 6 West Wairarapa Fault. 7 Crossover Fault between West Wairarapa and Alfredton Faults. 8 CartertonFault. 9 Very straight valley incised along strike into mudstone. 10 No cause apparent on ground, probably shadowing. II Escarpment. F, Correspond to fault lines mapped on sheet 12 R, Minor road. C, Ridge crests.
tural features were displayed by the satelliteimagery. A large curvilinear feature to the east ofGladstone (see Fig. 1) fits into this category. Thisfeature, mildly expressed in the stream pattern onthe topographical map (NZMS 1 1:63360, NI62),was clearly visible in most of the image enhancement options. Field investigation showed the feature to be a pair of gorges, deeply incised into asequence of Lower Cretaceous sandstone and siltstone, and separated by a sharp, narrow ridge.Although its cause is unknown, the feature is nearto a fault which separates this sequence from siltstone and sandstone of Miocene age and thus maybe a structural feature such as a flexure of the crust.
The black and white images were easier to use
than the colour ones, and appeared to contain moreinformation. This may be due in part to the greatvariety of land use giving the colour image toomany tonal variations. The stretched colour composites were also less satisfactory,as was the ratioedimage. There are a number of ways bands can becombined to form a ratioed image, so it may bethat a different formula could result in a more useful product for identification of subtle linearfeatures.
Field checks
Masterton/Mauriceville area
Figure 3 summarises the result of our ground truth
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364 New Zealand Journal of Geology and Geophysics, 1985, Vol. 28
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Fig. 4 Ground truth surveyresults of the linear featuresmapped around the AorangiRange/Palliser Bay/Martinborough area. Of these linear features, 46% have been identified,19% are fault traces, and 12% areresistant sandstone ridges of theTe Munga Formation.
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I West Waitutuna resistant sandstone ridge. 2 Bull Hill resistant sandstone ridge. 3 Te Munga resistant sandstoneridge. 4 Kupes Sail Fault. 5 Black Rock Point resistant sandstone ridge. 6 Crush zone at Ngawi marking probablefault. 7 River Valley in Whatarangi Formation. 8 Dry River Fault. 9 Fault. 10 Otaraia Fault. 11 Dry RiverFault. 12 Te Munga Fault. 13 Otaraia Fault. 14 Dry River Fault. 15 Ruakokoputuna Fault. 16 Southern endof Ruakokoputuna Fault. 17 Clay Creek Fault. 18 Series of northwest-trending gullies running off an escarpment. 19 Cliff face marking an edge of the Hawera Series. 20 Resistant sandstone ridge (Mt Ross). 21 Resistantsandstone ridges. 22 Very straight river courses. 20-22 were not visited in the field but inferred from map checksand personal communications.
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Belliss et al.-Linear features, Wairarapa
Fig. 5 Linear features identifiedby comparison with the 1:63360Tinui-Awatoitoi map sheet(Johnston 1975). 35% of the linear features mapped here markfaults.
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365
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0/}1Jo .....•.•...··,·.··.·•••~.·l~ •••••••,••••••••••••••1 Bute Fault. 2 Marangai Fault. 3 Part of the Carterton Fault. 4 Tawhero Syncline. 5 Aupiripiri Fault. 6 Fault. 7Fault. 8 Fault. 9 Fault. 10 Fault-part ofthe Mataikona Fault? 11 Fault. 12 Mataikona Fault. 13 WhakatakiFault. 14 Fault. 15 Fault branching off Mataikona Fault. 16 Tinui Fault. R, River.
survey in this area. Most of the major faults werepicked up on our linear feature maps but only alongparts of their traces.
On fiat areas with some alluvial coverage, Landsat has not showed up the traces of major activefaults at all well, although they are clearly visibleon the ground. It was suspected that these tracesmay have shown up in an image taken during aparticularly dry season, when vegetation would bemoisture stressed; vegetation along water courses,in irrigated areas, and along the fault lines, wouldshow up healthier (darker tones) than elsewhere.For example, on a colour composite of PEL 320,an image recorded on 20 January" 1979, the Carterton and Mokonui Faults are clearly visible. Onboth traces, vegetation on the downthrown side ofthe fault shows up as dark red. For this particularinstance, a colour composite image would be thebest image product to use. It is in the rolling hillcountry to the north of Masterton that the best correlation between Landsat linear features and recognised topography and structure has been achieved.
Aorangi Range/Martinborougli area
The overall structural trend in this area is of northeast-southwest trending faults, ridges, and valleys.This trend shows up well in our linear feature map(Fig. 4), but our linear features rarely coincided withfault traces. Again, the sun angle emphasised features at right angles to this trend, particularly gullies running off resistant sandstone escarpments.They tended to be shorter than the more northeast-southwest linear features, so could be largely
discounted. However, where several gullies and,perhaps, stream beds, lined up across the image,we have recorded linear features, but doubt if thereis any evidence to support their existence.
However, the linear feature maps do show several groups of small linear features running rightacross the Wairarapa area (see Fig. I) and, locally,onto the west of the Wellington Fault. Some of thesemay represent traces of an ancient or secondaryfracture pattern; most, however, are probably coincidental alignments of a variety of features.
In the very rough country of the Aorangi Range,shadowing is very marked, and a higher sun anglemay have enabled the pattern of fault traces to showup better.
Tinui-A watoitoi area
Approximately the lower one-third of Johnston'smap is included on this Landsat image. Althoughthe image is spotted with clouds, there are a number of linear features visible, and some of thesecorrespond to major faults (Fig. 5). As with 'the twofield-checked areas, only parts of the traces are visible. This area was not field checked and, instead,Johnston's map was compared directly to our linear feature map.
CONCLUSIONS
Of the four questions asked:I. Approximately 50%oflinear features mapped
were located by ground survey. 30-35% of thesecan be classed as structural lineaments.
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366 New Zealand Journal of Geology and Geophysics, 1985, Vol. 28
2. Based on the two areas that were ground surveyed, at least 50% of the major faults evident onthe ground are visible on the satellite imagery. Ifall known faults are included, this figure falls to20%. We would expect this figure to rise for thisparticular image, if it had been taken at a moresuitable sun angle. Once digitised contours areavailable for New Zealand, PEL programs will havethe capability to produce shaded relief images withany sun elevation and azimuth.
3. If little is known about an area, a lineamentstudy is objective. As knowledge of the areaincreases, preconceived ideas influence what is seenand the study becomes subjective. Operators familiar with a study area will automatically look forfeatures they have already mapped in the field andthus are more likely to ignore features at variancewith current thinking. Comparison of the two linear feature maps drawn by separate operators (SEBand ADWF) gave very similar results (Fig. 2C, D).The major disparities were differences in lineamentlength (the tentative daub versus the bold slash)and line placement (ridges versus valleys). Slightdifferences in the distribution of the bearings of thelinear features in these two plots can be explainedby assigning an uncertainty of ±3° to the measuredangles.
4. The best image to use, for an area like Wairarapa with varied topography, is band 4, with a 7X 7 high pass filter, an add back factor of one, andstretched. This particular enhancement, however,was best in rolling hill country, not so good in steepterrain, and poor on flat alluvial areas. Stretchingthe data is definitely better than histogram equalising it. A smaller study region is more likely to bea topographically homogenous area. This wouldallow stretch program values to be tailored to bestsuit that particular terrain.
For future linear feature studies, we recommendthe linear features should be transferred fromLandsat images to topographic maps beforecommencing fieldwork. Although this may introduce inaccuracies in the positioning of the linearfeatures, it would be a minor complication in comparison to trying to locate an exact position fromthe small scale of a Landsat image.
ACKNOWLEDGMENTSWe thank Dave Francis and Terry Bates for assistance inthe field; the numerous people who critically reviewed themanuscript; Dean Hammond for drafting the figures; andthe word processing staff of the Physics and EngineeringLaboratory, DSIR, for figuring out all the drafts.
REFERENCESBates, T. E. 1967: The geology of the Northern Aorangi
Range and part of Palliser Bay. Sheet N165.Unpublished MSc. thesis, held at Victoria University of Wellington Library. 216 p.
Cardamone, P.; Casnedi, R.; Cassinis, G.; Cassinis, R.;Marcolongo, B.; Tonelli, A. M. 1976: Study ofregionallinears in central Sicily by satellite imagery.Tectonophysics 33: 81-96.
Csillag, F. 1982: Significance of tectonics in linear featuredetection and interpretation on satellite images.Remote sensing ofenvironment 12: 235-245.
Johnston, M. R. 1975: Sheet NI59 and pt NI58-TinuiAwatoitoi. Geological map of New Zealand1:63360. Wellington, Department ofScientific andIndustrial Research.
Kingma, J. T. 1967: Sheet 12-Wellington. Geologicalmap of New Zealand 1:250000. Wellington,Department of Scientific and Industrial Research.
McDonnell, M. J.; Pairman, D. 1982: Physics and Engineering Laboratory image processing system documentation manual. PEL DS1R manual no. 264.
McDonnell, M. J.; Pairman, D.; Fowler, A. D. W. 1983:Overview of PEL image processing capability. PELDS1R report no. 827.
Moore, G. K.; Waltz, F. A. 1983: Objective proceduresfor lineament enhancement and extraction. Photogrammetric engineering and remote sensing 49(5): 641-647.
Norman, J. W. 1969: Linear geological features as an aidto photogeological research. Photogrammetria 25 :177-187.
Ostaficzuk, S. 1981: Megalineaments as evidence of someglobal tectonic phenomena. Bull de'AcademiePolonaise des Sciences Sdrie des Sciences de la TerreVol. XX1X(12): 143-155.
APPENDIX 1
Notes on image enhancement techniques used in the Wairarapa linear feature study
1. Histogram equalisation, stretching and destriping
All Landsat images are received in four spectral bands oncomputer compatible tape. Each spectral band consists ofa series of numbers representing radiance values at eachpicture element or pixel. The initial data range is 0-127for bands 1-3, and 0-63 for band 4. The aspect of theimage which is of interest (e.g., land) normally occupiesonly a portion of the available range. Before the image isdisplayed, the radiance range of interest needs to be redistributed over the range 0 (black) to 255 (white). The mostcommon algorithm for doing this is histogram equalisation. This uses a nonlinear look-up table to produce anoutput image with uniformly distributed grey levels.
Stretching is a more straightforward enhancement technique. It uses a linear, instead of a nonlinear, look-uptable to enhance the range of the input histogram that isof interest. For example, the histogram below (Fig. 6) canrepresent our original scene. If it was histogram equalised, the resulting scene histogram should approach thestraight line. If it was stretched, the start and stop points
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Belliss et al.-Linear features, Wairarapa 367
Fig. 6 The effect on a scene histogram of stretching orhistogram equalising digital data.
of the histogram would be taken out to 0 and 255,respectively, and the histogram would retain more of itsoriginal outline.
A stretch program may also take the ends of the histogram out past 0 and 255. When this is done, the histogram is said to have been clipped. Usually a histogramwill not be clipped by more than 5%.Stretching an imagehelps to display features in the middle range of radiancevalues.
For enhancing filtered images, we found stretchingpreferable to histogram equalisation.
Landsat images contain a six-line striping which is acharacteristic ofthe multispectral scanner. This is removedwith a destriping algorithm before any other processingis carried out.
Origional scene histogram
Ideal histogram equalised result
.- Histogram of origional scene once stretched
2. FilteringLow pass filtering is accomplished using a box filteringalgorithm which, for each input pixel, replaces its (radiance) value with a value averaged from those within arectangular box centred on that input pixel. This "blurs"the image.
High pass filtering involves taking, pixel by pixel, theweighted difference between the original image and thecorresponding low pass filtered image. That is, if p = anoriginal pixel value, I = its low pass filtered value, V =the resulting filtered value, then, for a normal high passfilter (HPF), V = p(l +x) - lx, where x is an add backfactor which increases from zero with the strength of thefilter. The filter sharpens the edges of image features.
For a direct high pass filter (DHPF), V = P - I + c,where c is an additive constant (usually 127).
3. Band ratioingBand ratioing is an enhancement technique which suppresses the effect of topography within an image toemphasise intrinsic surface characteristics. It is achievedby ratioing the pixel values in each of three bands toanother band or composite band to obtain the new valueof each pixel. This "simplifies" the image by removingbrightness variations due to topography. For example,taking a normal scene: if a pixel in a bright area has valuesof, say, 10 in band I, 20 in band 2, and 40 in band 4,and a pixel in a similar shaded area has, correspondingly,5, 10, 20, both become equal,
10, 20, 40 5, 10, 20i.e., 70 and 35 both equal 1/7, 2/7, 4/7.
For this to work well, it must be assumed that eachspectral band has been radiometrically calibrated. Toensure that black in the image corresponds to zero, hazemust be compensated for. We do this by forcing the minimum value in each band to zero. This zero (black) willcorrespond to an area of shadow or clear water.
255Pixel valueo
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