POTENTIAL OF DENSE MATCHING FOR THE GENERATION OF HIGH QUALITY DIGITAL ELEVATION MODELS

Transcription

1 POTENTIAL OF DENSE MATCHING FOR THE GENERATION OF HIGH QUALITY DIGITAL ELEVATION MODELS Mathas Rothermel, Norbert Haala Insttute for Photogrammetry (fp), Unversty of Stuttgart, Geschwster-Scholl-Str. 24D, D Stuttgart, Germany KEY WORDS: DEM/DTM, Surface, Pont Cloud, Image Matchng, Geometry, LIDAR ABSTRACT: Untl recently, the acquston of hgh qualty Dgtal Elevaton Models was domnated by the use of arborne LDAR. However, the ncreasng qualty of dgtal arborne cameras n combnaton wth recent mprovements n matchng algorthms meanwhle allow for the automatc mage based collecton as a sutable alternatve. Wthn the paper, these progresses wll be demonstrated on the example of photogrammetrc DEM generaton usng the Sem-Global Matchng (SGM) stereo method. Snce ths approach ams at a pxel-wse matchng, dense 3D pont clouds can be generated. The tests descrbed n the paper are based on data collected from dfferent dgtal arborne cameras at varous flght scenaros durng a recent test on photogrammetrc 3D data capture. By these means, the mpact of dfferent stereo confguratons on the qualty of the fnal outcome can be evaluated and compared to already avalable test results. Specal nterest s also pad to the analyss and combnaton of multple stereo mage pars wth dfferent baseto-heght ratos, whch can be used effcently to ncrease the accuracy and relablty of the matchng result. 1. INTRODUCTION Dgtal mage matchng for automatc pont transfer s a wellknown standard procedure wthn photogrammetrc software tools. However, n contrast to the great relevance of mage matchng wthn automatc aeral trangulaton, the mportance of ths technque for 3D surface reconstructon has long been subordnated. Especally whle amng at very accurate and dense Dgtal Surface Models (DSM), mage based surface reconstructon was frequently outpaced by arborne LDAR. Meanwhle ths gap s dmnshng. As an example, dgtal aeral cameras can provde hghly overlappng arborne magery of good dynamc and sgnal-to-nose-rato as standard data sets. Ths s hghly benefcal for automatc mage matchng especally for surfaces wth relatvely lttle surface texture. Consequently, the qualty and accuracy of mage based pont transfer as basc observaton for 3D surface reconstructon amelorated consderably, as also verfed wthn recent tests (Haala et. al., 2010). Thus, dgtal mage matchng establshes as a vald alternatve to arborne LDAR. The current comeback of mage based DSM generaton addtonally trggered a renassance n dedcated software developments. Wthn exstng commercal software tools, stereo mage matchng usually apples algorthms for feature extracton and matchng. Ths approach s potentally fast and relable, but can lead to an nhomogeneous dstrbuton of matched ponts. Regons wth a rather lmted number of 3D ponts can especally occur n areas of low mage texture. Ideally, the DSM resoluton should only be lmted by the ground samplng dstance of the avalable magery. However, ths requres a matchng result for each mage pxel. In order to cope wth the general ambguty of such a per-pxel measurement, addtonal constrants, such as the assumpton of a smooth surface are usually ntroduced. Algorthms that globally mnme matchng costs between correspondng pxels and the respectve smoothness constrants are called global mage matchng. Whle they provde good results n terms of qualty and resoluton, they usually suffer from a hgh complexty, whch results n rather low performance. However, ths computatonal complexty can be reduced sgnfcantly by the Sem-Global Matchng (SGM) stereo method as proposed by (Hrschmüller, 2008). Ths approach, whch wll be used durng our nvestgatons, approxmates a global approach by mnmng matchng costs, whch are aggregated along a certan number of 1D path drectons through the mage. Snce dsparty jumps are prevented by penaled by addtonal costs, smooth dsparty courses along the paths and thus to homogeneous surfaces are based. The pxel-wse SGM approach provdes a dense pont dstrbuton, whle the global approxmaton on paths enables a reasonable runtme on large magery. The potental of the algorthm was already demonstrated for dfferent applcatons and data sets, ncludng aeral mages, satellte data or vdeo sequences. Inspred by these promsng results, the Sem-Global Matchng method was mplemented by the authors, ncludng the Mutual Informaton matchng cost calculaton, the cost aggregaton step, the dsparty postprocessng procedures and a trangulaton nto object space. Wthn the paper, an accuracy and performance evaluaton of ths algorthm wll be presented. The nvestgatons are based on datasets from the recent project on Dgtal Photogrammetrc Camera Evaluaton, whch was ntated by the German Socety for Photogrammetry, Remote Sensng and Geonformaton (DGPF). It contans magery from several large format aeral cameras flown on the same test ste at two flyng heghts (Cramer, 2010). For comparson, data from a LDAR system s addtonally avalable. Wthn the paper, the basc prncples of the mplemented SGM approach are brefly ntroduced n secton 2. The man part of the paper n secton 3 then evaluates the potental of ths algorthm for mage based dense DEM generaton for several confguratons. By analyss of multple stereo mage pars wth dfferent base-to-heght ratos the general trade-of between good ntersecton geometry for large base-to-heght ratos and

2 smplfed matchng due to greater smlarty of mage content for short baselnes s evaluated. The matchng accuracy for these dfferent stereo mage confguratons s determned for test areas defned by a planar sports feld and a bult-up area of hgher geometrc complexty. The avalablty of hghly overlappng magery s addtonally used for consstency checks to evaluate matchng qualty and elmnate erroneous matches. These nvestgatons based on redundant 3D pont measurement from multple stereo pars are also used to evaluate the potental of SGM for dfferent camera systems and llumnaton condtons as avalable from the DGPF test data set. These results are also compared to pont clouds from arborne LDAR and the commercal software tool MATCH-T DSM as a reference. 2. DENSE DEM GENERATION Wthn ths secton, the bascs of the mplemented Sem-Global Matchng approach and the subsequent post-processng wll be presented 2.1 Sem-Global Matchng Our mplementaton of the SGM algorthm n large extent s smlar to (Hrschmüller, 2008). The am of ths pxel-wse matchng s to relate each pxel coordnate p n the base mage to ts correspondng pxel coordnate q n the match mage. Each relaton ( p, q) nduces a matchng cost. The sum of all costs defnes the global matchng cost whch s assumed to be mnmal for optmal mage algnment. Snce the problem of mnmng global matchng costs for 2D mages s known to be NP-hard, thus, the dea of the SGM s to mnme an approxmaton of the global cost. m p1 p 2 p p 3 4 p5 (a) m C, j ( p, dj ) (c) (d) Fgure 1 (a): Base mage pxels p (b): Potental correspondences q3, j of p3 n the match mage (c): Costs c 1.. 5, j assgned to the 3D cost structure (d): exemplary mnmal cost path along the mage path r k As also depcted n Fgure 1, for each base mage pxel p the matchng costs c, j( p, q, j) for a set of D potental correspondences q, j 1,..., D n the match mage are calculated. Usng the exteror and nteror camera orentatons from bundle block adjustment, the eppolar lne e( p) nduced n the match mage by p can be determned. Thus, the search for potental n n q3,1 q q 3,2 3,3q3,4q3,5 (b) r k correspondng pxels can be lmted to q, j e( p, dj). The dsparty d j, specfes the actual poston on e and therefore the parallax. The mnmal costs c, j( p, q, j) of the set of potental correspondences defne a frst estmaton of the dsparty. Unfortunately, these cost mnma often are not dstnctve and result n wrong parallax estmatons. Ths problem can be solved by cost aggregaton. For ths purpose a N M D 3D cost structure contanng the costs c, j( p, d, j) s assembled. It contans the matchng costs of N M base mage pxels and ther D potental correspondences n the match mage. The fnal aggregated matchng cost s( p, d, j) of a base mage pxel and ts potental correspondence s derved by a weghted summaton of mnmal costs along 16 mage paths r endng n k c, j( p, d, j). Thereby penalty terms are ntroduced to force these cost paths to be smooth. However, dstnctve mnma mantan the possblty of non-contnuous paths. These accumulated costs represent an approxmaton of the global costs. The fnal correspondence q of a base mage pxel p, and therefore the parallax, s defned by the mnmum of ts aggregated costs mn s( p, q, j). Sub-pxel accurate j dsparty estmatons are derved by quadratc curve fttng and results are stored n a dsparty mages. Wthn all tests the Mutual Informaton (MI) matchng cost was used. MI s based on entropes and jont entropes and can be used as a measure for the smlarty of two mages. Correspondences are chosen such that the MI of two mages respectvely ther smlarty s maxmed. 2.2 Object pont trangulaton and mult-stereo matchng The matchng estmates parallaxes, whch lnk correspondng pxels between two mages. Snce nteror and exteror orentatons are known from AT, the coordnates X of the correspondng object pont can be computed by trangulaton. Ths problem can be formulated as lnear homogenous system AX = 0 as descrbed n (Hartley et. al., 2004), whch s solved by a least squares estmaton. By matchng overlappng mages redundant measurements x of the same object pont are obtaned. Matchng n mages wth the same base mage results n n 1mage ponts for object pont X. All measurements can be related usng eppolar geometry and the dsparty estmatons derved by SGM. Agan, the trangulaton problem can be formulated as over-determned lnear homogenous system and solved usng least squares technques. Reprojectng X nto the mages results n the mage coordnates xˆ. If the reprojecton error xˆ x s larger than a base-to-heght rato 2 dependent threshold, the measurement x s regarded as nonvald and s dscarded. Iteratve trangulaton and evaluaton of reprojecton errors lead to the fnal object coordnates X. Latter strategy wll be referred mult-stereo matchng. 2.3 Elmnaton of msmatches Despte the flterng of erroneous measurements wthn the mult-stereo approach as descrbed n the secton before, addtonal flters were appled to remove wrong dsparty estmatons. Frst a consstency check s performed by smply nterchangng the roles of base and match mages for mage matchng. Only dsparty estmatons consstent to ths forwardbackward matchng are consdered as vald. Addtonal

3 erroneous dsparty estmatons are removed wthn flterng the dsparty mages by conservatve smoothng (Jan, 1986) and a subsequent occluson check (Hrschmüller, 2008). 3. PERFORMANCE OF SEMI-GLOBAL MATCHING For all our nvestgatons presented n ths paper mage data from the DGPF project for evaluaton of photogrammetrc aeral camera systems was used. Ths test data set conssts of magery from several dfferent arborne camera systems wth nomnal ground samplng dstances (GSD) of 20 and 8 cm (Cramer, 2009). However, for reasons of smplcty our tests were lmted to 8cm GSD magery. secton 3.4. Fnally, the potental ncrease of completeness for the reconstructed pont clouds by usng multple base mages and fusng the resultant pont clouds s dscussed n secton 3.5. DMC UltraCamX RMKTop15 Fgure 2: Test regon Sportsfeld wth planar surface and homogenous texture. The frst test area Sportsfeld depcted n Fgure 2 s a planar football ground, already used for evaluatons of commercal matchng software (Haala et. al., 2010). Its smple geometry eases accuracy evaluatons, whch were addtonally compared to LDAR data as captured usng Leca s ASL50. Snce t features rather low surface texture, t s also very well suted to evaluate the performance of matchng approaches for potentally challengng areas. The basc stereo matchng provdes two correspondng mage coordnates. However, to mprove the accuracy of the respectve object pont, multple matches can be merged by usng redundant measurements for 3D pont trangulaton. In order to nvestgate effects of dfferent base-to-heght ratos and to demonstrate such benefts of mult-stereo matchng, four mage pars wth varyng base lengths of m at a constant flght heght of 1200m were used for mult-stereo matchng and nternal accuraces are analysed n secton 3.1. These nvestgatons on varyng base-to-heght ratos are completed n secton 3.2 by usng magery of more complex geometrc structures. As t s vsble n Fgure 3, the second test area Castle provdes such structures. It conssts of complex roof geometres, planar surfaces and vegetaton as trees and vneyards. Secton 3.3 evaluates the robustness of SGM regardng dfferent sensors and flght specfc varances as llumnaton changes, whle a comparson of SGM to the commercal software tool MATCH-T (Lemare, 2008), whch apples feature-based matchng algorthms s presented n Fgure 3: Test regon Castle wth complex geometres and dversfed texture. 3.1 Accuracy mprovement by mult-stereo matchng In a frst test the benefts of mult-stereo matchng regardng pont densty and absolute accuracy was examned. Therefore fve UltraCamX mages of the same flght strp depctng the test area Sportsfeld were matched. Pont clouds were generated for sngle stereo matchng results (Confg.1&2, Fgure 4) and usng the mult-stereo approach (Confg.3&4, Fgure 4). Obvously, the 3D reconstructon of a planar surface s rather benefcal for the SGM algorthm snce t can be enforced by settng large values for the smoothness constrant. In order to guarantee adequate smoothness settngs, the adjacent area of the sports feld was matched such that a suffcently detaled surface was obtaned. The correspondng penalty settngs were used throughout ths test. In order to evaluate absolute accuraces, pont clouds derved by SGM are compared to LDAR data. Therefore a plane was ftted nto the LDAR pont cloud. In order to elmnate outlers, the standard devaton of the pont-to-plane resduals r was computed and all ponts for whch r 3 were dscarded. Snce the feld possesses rather small dfferences n heght, resduals between LDAR ponts and the estmated plane can be approxmated by dfferences of ther vertcal components. The fltered LDAR measurements were used to estmate the fnal reference plane. SGM pont clouds were compared to ths reference plane. After trangulaton, outlers were removed usng the same approach as for the LDAR data. Confg.1: Confg.2: Confg.3: Confg.4: Fgure 4: Accuraces of raw and fltered pont clouds derved by stereo and mult-stereo matchng.

4 Resultng standard devatons for raw and fltered pont-to-plane resduals are dsplayed n Fgure 4. Large values for the unfltered are a result of msmatches. For the mult-stereo confguratons 3 and 4 standard devatons of raw and fltered resduals are almost dentcal. Ths demonstrated that msmatches are removed effcently wthn the mult-stereo matchng approach. Furthermore, absolute accuraces can be mproved from 10cm to 5cm by ncorporatng redundant measurements. 3.2 Influence of varyng base-to-heght ratos In order to examne the nfluence of dfferent base-to-heght ratos on SGM, four mage pars were matched wth base-toheght ratos varyng from to 0.5. Imagery was captured by the UltraCamX, provdng a GSD of 8cm. The test area depcts a castle surrounded by vegetaton (Fgure 3). Three pont clouds were derved from the four stereo models. Thereby each pont cloud s trangulated ncorporatng dsparty estmatons of two stereo models. The respectve mage confguratons and correspondng pont clouds are dsplayed n Fgure 5. Flterng as dscussed n sectons 2.2 and 2.3 was appled and reconstructed ponts whch nduce reprojecton errors larger than 0.3 pxels were elmnated. Trangulaton of object ponts from two stereo models s convenent for evaluaton purposes snce the lnear homogenous system for object pont computaton s over-determned. As a result standard devatons of object ponts coordnates can be estmated by evaluatng the covarance matrces of the leastsquares soluton. In the followng planar and vertcal standard devatons are denoted by xy and. Confg.1 Confg.2 Confg.3 Fgure 5: Camera confguratons and correspondng pont clouds; Red and blue rectangles mark the base respectvely match mages. Large base-to-heght ratos ental ncreased dssmlarty of base and match mages. The man reasons are changes n perspectve and varances n llumnaton. As a consequence mage matchng performs worse and the number of successfully matched ponts sgnfcantly decreases (Fgure 5). Snce the mplemented flter algorthm requres an object pont to be detected n at least three mages, the number of reconstructed ponts s lmted mostly by the success rate of the wde base-lne mage par. As an example for Confg.1 success rates of matchng close and wde baselne mage pars amount 82% and 60%, respectvely. After flterng wthn the mult-stereo approach only 48% of all ponts reman. On the other hand the geometrc confguraton for large base-to-heght rato magery s advantageous and accuracy of trangulaton can be mproved. As vsble n Fgure 6, wth ncreasng base-to-heght ratos standard devatons n object space are decreasng. Thus, the benefcal geometrc propertes compensate worse performance of SGM. However, wde-baselne results are rather ncomplete and contan a larger number of msmatches whch are not elmnated by the flters. Matchng performance s evaluated usng error propagaton. Therefore standard devatons are f B transformed nto mage space by I 2. H Confg.1: Confg.2: Confg.3: Fgure 6: Standard devatons xy, and number of successfully trangulated ponts for camera confguratons 1-3. Respectve standard devatons were calculated for small baselne mage pars of each confguraton. It has to stay n mnd that object ponts were derved usng two stereo models and absolute values do not represent the actual accuracy of SGM. 3.3 Varyng sensors and llumnaton condtons In ths secton the robustness of SGM regardng dfferent sensors and flght specfc varances as llumnaton condtons s examned. All tests were carred out on the test area Sportsfeld. SGM stereo models were generated usng magery of the three camera systems UltraCamX, DMC and RMKTop15. As already dsplayed n Fgure 2 all mages possess rather low texture. Partcularly data of the UltraCamX offers only rather homogenous ntenstes. Sensor DMC Ultra- CamX ALS Base-to-heght rato Densty Pts/m after flter [cm] no flter [cm] Mean after flter [cm] I [px] Table 1: Results for test area Sportsfeld based on SGM and 8cm GSD magery, base-to-heght ratos For each system, mage pars provdng comparable base-toheght ratos of 0.25 and 0.5 were matched. The same penalty settngs were used throughout ths test for all camera platforms. As n prevous nvestgatons SGM pont clouds were compared

5 to a reference plane ftted nto the LDAR data. Agan, pont-toplane resduals and the correspondng unbased standard devatons were calculated and outlers for whch resduals are larger than 3 were removed. Eventually resduals and correspondng standard devatons of fltered ponts were computed. Results for base to-heght ratos of 0.25 are lsted n Table 1. The mean values of fltered pont clouds are n the range of errors nduced by the bundle block adjustment (Jacobsen et.al. 2010). Standard devatons are n the same range whch means accuracy largely depends on the results of the aeral trangulaton. As DMC magery provdes some texture and a small sgnal-to-nose-rato, the nose of the matchng results s lmted. Matchng of UltraCamX magery fals n some regons of the sports feld whch results n lower pont denstes. Ths s due to homogeneous ntenstes whch probably are a result of unfavourable llumnaton condtons. Ths clarfes the mportance of dversfed texture respectvely radometrc resoluton for SGM. However, the number of reconstructed ponts for both systems s sgnfcantly larger than measurements obtaned by LDAR. As n the prevous test, matchng accuracy n mage space was derved by error I propagaton. As only one stereo par s matched I represents the actual matchng accuracy of SGM wth absolute values smaller than 0.2 pxels. Matchng wde baselne mage pars s unfavourable snce t can result n low pont densty and frequent msmatches. Nevertheless, magery of the RMK s only avalable at base-toheght ratos of Therefore, SGM was evaluated for magery of all three camera systems at comparable base-toheght ratos. Results are dsplayed n Table 2. As dscussed n secton 3.2, decreasng performance of mage matchng can be compensated by better geometrc propertes of the mage confguratons. The same effect s observed wthn ths test. As expected, SGM for dgtal magery outer performs ts analogous counterpart regardng accuracy snce the smaller sgnal-to-nose rato cause larger standard devatons. However, a matchng accuracy of 0.31 pxels s acheved and derved pont clouds are rather dense. Sensor DMC Ultra- CamX RMK Base-to-heght rato Densty Pts/m after flter [cm] no flter [cm] Mean after flter [cm] I [px] Table 2: Results for test area Sportsfeld based on SGM and 8cm GSD magery, base-to-heght ratos Comparson of results MATCH-T and SGM In ths secton addtonal pont clouds of the test area Sportsfeld were derved usng the commercal software MATCH-T. Latter attacks the correspondence problem usng feature-based and least-squares matchng technques. In comparson to our SGM results, the commercal tool ncorporates all avalable magery for object pont generaton. In contrast, for pont clouds derved by SGM only 1 to 3 stereo pars were matched and results were merged wthn the multstereo procedure. SGM was parametered by the standard values as descrbed n secton 3. Agan, accuracy was evaluated by comparng resduals of the generated ponts to a plane ftted nto the LDAR data. Fgure 7 dsplays all pont clouds derved by SGM and MATCH-T. As the matchng success rate of MATCH-T sgnfcantly decreases for RMK magery, SGM seems to be pretty robust regardng the reduced sgnal-to-nose rato of the analogous camera system. It provdes a rather complete reconstructon and a standard devaton of 4.6cm. Due to homogenous texture SGM fals n some regons for the UltraCamX magery. Successfully reconstructed ponts provde a standard devaton of 5.2cm. DMC UltraCamX RMK SGM - 2 mage pars SGM - 5 mage pars SGM - 1 mage par MATCH-T MATCH-T MATCH-T Fgure 7: Reconstructed pont clouds for the test area Sportsfeld The feature-based approach mplemented n MATCH-T seems to be more robust regardng homogenous ntenstes n ths example. Unformly dstrbuted object ponts are reconstructed, provdng an accuracy of 7.1cm. Both methods yeld best results for the DMC magery. Dense surfaces can be reconstructed resultng n pont denstes of 102.9pts/m 2 respectvely 23.9pts/m 2. Standard devatons of pont-to-plane resduals amount 3.4cm for the feature-based approach and 2.7cm for the SGM method. It has to stay n mnd that due to ts black box character parameteraton s lmted and MATCH-T mght not perform at ts optmum. Furthermore, due to dfferent weather and llumnaton condtons durng acquston of the DMC and UltraCamX magery ths does not allow for a comparson of the dfferent dgtal camera systems, but demonstrates the capablty of the matchng algorthms at areas of very homogenous texture. 3.5 Combnaton of pont clouds from dfferent vewponts The UltraCamX dataset provdes magery wth overlaps of 80% n and 60% cross flght drecton. Therefore object ponts are

6 detected n at least n 10 mages. Wthn the mplemented multstereo matchng strategy an object pont s requred to be determned n at least three mages to be vald. Moreover, only object ponts vsble n the base mage can be trangulated. Therefore addtonal ponts whch appear only n the match mages due to vewpont changes cannot be reconstructed. Ths s a hard restrcton especally when matchng mages of neghbourng flght strps. Furthermore, base-to-heght-ratos of mage pars from dfferent flght strps are generally larger than for same-strp magery. As shown before, ths leads to a decrease of matchng performance and completeness. To overcome ths problem, n-strp magery of three adjacent flght strps were matched and resultng pont clouds were merged n object space. Enhanced models for the test area Castle and utled mage confguratons are shown n Fgure 8. (a) (b) Fgure 8 (a): Pont cloud derved by SGM usng mages of a sngle flght strp; (b): Combnaton of pont clouds generated usng magery of three flght strps; test area Castle, Ultra- CamX, 8 cm GSD 4. CONCLUSIONS Durng our nvestgatons SGM proved as a robust and easy to parametere matchng algorthm. Best matchng results were obtaned for stereo mages wth short baselnes, good texture and small sgnal-to-nose ratos. Obvously, matchng performance depends on the mage content, snce homogenous ntenstes and large sgnal-to-nose ratos can lmt the qualty of the generated 3D pont clouds. Stll, matchng accuraces better than 0.2 pxels at pont denstes better than 80pts/m 2 or 60% of the avalable GSD were feasble even for a very low textured sports feld. Potentally, the matchng accuracy and relablty decreases for large base-to-heght ratos due to changes n perspectve and llumnaton. Nevertheless, the benefcal geometrc propertes for larger baselnes at least partally compensate the reduced matchng accuracy. Msmatches, whch occur more frequently for large baselne mages, can be elmnated effcently durng the mplemented mult-stereo matchng. However, ths outler flterng of course reduces the densty of generated pont clouds. For ths reason, the combnaton of several stereo mage pars to multple parallax estmatons s especally benefcal. The combnaton of multple measurements durng trangulaton ncreases the accuracy of the generated 3D pont clouds whle ther completeness can be ncreased by mult-stereo matchng of magery wth varyng perspectve. Durng our tests magery from two dgtal sensors UltraCamX and DMC and the analogue camera RMKTop15 were performed. By these means the robustness of SGM wth respect to dfferent sensors and flght specfc varances of llumnaton could be demonstrated. Durng our tests, despte the fact that methods of post-processng mght vary and have sgnfcant nfluence on the matchng performance, SGM mpressvely proved ts potental for the generaton of hgh qualty Dgtal Elevaton Models. 5. REFERENCES Cramer, M., Haala, N., DGPF project: Evaluaton of dgtal photogrammetrc aeral based magng systems overvew and results from the Plot Centre. In: IAPRS, Vol. XXXVIII, Part 1-4-7/W5, on CD-ROM. Cramer, M., The DGPF-Test on Dgtal Arborne Camera Evaluaton Overvew and Test Desgn. Photogrammetre - Fernerkundung Geonformaton (PFG). Heft 2(2010), pp Haala, N., Hastedt, H., Wolff, K., Ressl, C. & Baltrusch, S., Dgtal Photogrammetrc Camera Evaluaton - Generaton of Dgtal Elevaton Models. Photogrammetre - Fernerkundung Geonformaton (PFG). Heft 2 pp Hartley R.I., Zsserman A., Multple Vew Geometry n Computer Vson, Cambrdge Unversty Press, Cambrdge, Chap.12. Hrschmüller, H., Stereo Processng by Sem-Global Matchng and Mutual Informaton. IEEE Transactons on Pattern Analyss and Machne Intellgence, 30(2), pp Jacobsen, K., Cramer, M., Ladstädter, R., Ressl, C., Spreckels, V., DGPF-Project: Evaluaton of Dgtal photogrammetrc Camera Systems. Geometrc Performance, Photogrammetre - Fernerkundung Geonformaton (PFG), Heft 2(2010), pp Jan, A., Fundamentals of Dgtal Image Processng, Prentce-Hall, New Jersey, Chap.7. Lemare, C., Aspects of the DSM Producton wth Hgh Resoluton Images. In: IAPRS, Volume XXXVII, Part B4, pp