Geometric Calibration of the CAMIS Sensor

Transcription

1 Geometi Calibation of the CAMIS Senso Abdullatif Alhath & James Bethel Geomatis Aea, Shool of Civil Engineeing Pudue Univesit Septembe 00

2 Pesentation Outline 1 Intodution: Reseah Objetives Senso Desiption Laboato wok: Site pepaation Measuements and adjustment in objet spae Captuing Images 3 Taget Loations in image spae Mathing: Coss-oelation mathing CCM Least squaes mathing LSQM

3 4 Mathematial Model: Mathematial model Solution method 5 Distotion Analsis: Radial Distotion Deenteing Distotion 6 Results and Disussion

4 1.1 Reseah Objetives CAMIS senso has been used in multispetal imaging and mapping puposes b mounting it in an aiplane with GPS and INS sstems. These auilia sensos povide ve good position and attitude data fo stabilizing the subsequent bundle blok adjustment. The aim of this wok was to make a laboato alibation fo the geometi paametes of the CAMIS senso.

5 1. Senso Desiption CAMIS stands fo Computeized Aibone Multiamea Imaging Sstem. CAMIS is a sstem fo aibone emote sensing and is designed to utilize moden solid-state imaging and data aquisition tehnolog. It onsists of fou o-boesighted aea-ccd ameas with band pass filtes: blue, geen, ed, and nea infaed. Eah senso has its own optis and obtains its own image independentl fom the othes at the same time. The senso is opeated b Topogaphi Engineeing Cente and we have woked with M. Mith Pieson to obtain the equied data. CAMIS, the fou ameas

6 CAMIS in Aiaft with Image Displa

7 CAMIS 3 Bands and Colo Composite

8 Mosai fom CAMIS Stips

9 .1 Calibation site pepaation: Tagets laout Site wok Taget design oss shape» So thei entes positions will be ead easil. Enlagement showing 5 tagets Tagets laout patten» This laout allows us to eove the needed geometi paametes and sstemati eos Eposue stations The senso was mounted on a leveled plate fied on a suve tipod whih is about 8m fom tagets fa enough to use infinit fous position Tagets laout

10 Site wok steps ont d. Measuements and adjustment in objet spae: Laboato measuements Measuements in the alibation site Two 3 a-seond aua theodolites wee stationed and efeened to measue dietions. taget entes theodolite loations amea ase monuments Camea Bod CCD Aa Font nodal point Sepaation.5 mm Steel tape and mahinist alipes to measue distanes Optial benh to detemine the loations of the nodal points Rea nodal point Note: font & ea nodal points ae evesed fom thei usual position oss setion of one amea showing the lenses, ea and font nodal points

11 Site wok steps ont d. Measuements and adjustment in objet spae ont d Netwok adjustment Having all these obsevations, we end up with an ove detemined sstem of equations. A bundle adjustment pogam was developed to adjust those oodinates of the tagets and the instument stations. As a esult of that, we detemined peisel all ou tagets and stations in the objet spae whih is a neessit fo the alibation pupose..3 Captuing Images This step was opeated b a team fom TEC and obseved b the Pudue team We tied to simulate the eal woking onditions b setting the lenses to the woking infinit fous position Images wee viewed at the site to make sue that as man as possible of the tagets wee eposed.

12 3 Taget Loations in Image Spae 3.1 Coss Coelation Mathing CCM A oss oelation mathing pogam was used to get ough appoimation of taget positions in the image spae to within a piel. image path v ideal template u This was done b omputing the similait between a window path ontaining the ideal taget and the anothe window fom the aptued image. Despite the fat that, the CCM esults showed that we ae onl awa fom the eat position b a piel o less, we needed moe auate and peise methods to define the eat loation within a hundedth of a piel o so. C uv N i 1 N i 1 u i u i u u v N i 1 v i i v v 1 / CCM Math

13 Response to Coase Alignment via Template Mathing

14 3 Taget Loations in Image Spae ont d 3. Least squaes mathing LSQM LSQM utilizes the fist deivative of the intensit in both and dietions to efine the best oespondene and the eat mathing an be eahed b moving one window with espet to the othe one while minimizing some of squaes of diffeenes of intensit values. The similait between the two spots was onl geometiall modeled sine the adiometi effet was eliminated. Get the appoimate loation of the imaged taget using the fist mathing appoah. Those loations should be within a few piels of the eat loation. A window aound that loation fom the image with adequate size will be etated. The ideal o template taget is etieved at this point. Similait in the intensit is enfoed between the two windows. the taget in Image path the etated taget mathing esults using two methods in suession

15 4 Math Model and Solution Method 4.1 Math Model The mathematial model was hosen aefull in ode to eove all signifiant soues of geometi eos and estimate all signifiant oetion paametes fo those eos. Samtane 1999 eploed this model in detail. It was deived fom the fundamental ollineait equations. It maps the oodinates fom the objet spae into the image spae though some paametes. Eteio paametes whih inlude the loation and oientation paametes Inteio paametes, lens distotion and foal length ae eamples of the seond tpe. o o f o o f

16 4 Math Model ont d The model speifiall oves and takes into aount the lens distotion though some paametes that model adial, deenteing, and affinit distotion. whee: : adial, deenteing, affinit distotion oeffiients p p k k k a a p p k k k , o o,, i k, i p i a

17 Eah taget obsevation will geneate two equations. Consequentl, the numbe of equations will be twie the numbe of tagets in the image fo eah amea f p p k k k F f a a p p k k k F 4 Math Model ont d

18 4 Math Model ont d 4. Solution Method In a alibation poess like this we want the numbe of equations to eeed the minimum equiement in ode to have an ovedetemined sstem. Suh a sstem enhanes the eliabilit and peision of the esult. In this poblem, 13 paametes wee estimated and the numbe of tagets that wee used was 0 and 1 in some ases. So, the edundan we had duing the poedue was 7. The Unified least squaes appoah was used to solve this sstem sine some a pioi knowledge is available fo a numbe of paametes. This a pioi knowledge is utilized to give those paametes initial values and weights. In this sense, some of the paametes wee teated as obsevations with low peision b assigned lage vaianes to them. Sine the sstem is non-linea, the paamete values will be updated iteativel until onvegene b adding the oetion veto

19 5 Distotion Analsis Afte detemining the amea paametes inluding distotion paametes, distotion uves wee dawn fo visual and omputational analsis. 5.1 Radial Distotion It is the displaement of an imaged objet adiall eithe towads o awa fom the piniple point k δ / k k 1 3 δ / The esulting uves wee obtained fo all fou ameas and the maimum adial distotion was less than 40 miometes. Radial distotion uve of the blue amea

20 5 Distotion Analsis ont d Eposue station Radial distotion uve equalization The following step was done to level o balane the uve based on equalizing the maimum and the minimum distotion values. This step has no effet on the final esults of the oeted oodinates; it is just osmeti but aepted pofessional patie. α α min α ma f Mathematiall, balaning the uve leads to a hange in the adial distotion paametes and onsequentl the foal length and othe elated amea paametes. So this poedue was done iteativel and the paametes wee updated. d ma d min CFL: Calibated foal length. CFL tan α CFL tan α ma ma min min CFL ma tan α tan α ma min min 0 image plane oss setion We want dma and dmin to have appoimatel the same magnitude.

21 5 Distotion Analsis ont d Radial distotion RD esulting uves. Saled RD enteed at FC fo the Blue amea Radial distotion Equalization iteation fo the Blue amea FC: fiduial ente. PPS: pinipal point of best smmet.. Saled RD enteed at PPS fo the Blue amea

22 5 Distotion Analsis ont d 5. Deenteing Distotion DD The misalignment between lens omponents will lead to sstemati image displaement eos whih is alled Deenteing Distotion.. Saled DD enteed at PPS fo the Blue amea δ p [ ] p o 1 o o δ p [ ] p o 1 o o. Saled DD enteed at FC fo the Blue amea

23 6 Results and Disussion Pa am ete f o Blue Camea Woking band 450nm Geen Camea Woking band 550nm Red Camea Woking band 650nm IR Camea Woking band 800nm mm mm mm mm mm mm mm mm o mm mm mm mm k 1 k k 3 p 1 p a a Estimated paametes of the fou sensos.

24 6 Results and disussion ont d Fo simpliit, the gaphial use intefae featue in MATLAB was used to eate a small use-fiendl pogam to show the esults and ompute efined image oodinates on a single point basis. The paametes of eah amea wee stoed in the file and b inseting the value of the measued line and sample and speifing the oesponding amea, the oeted line and sample will be alulated and pinted in the window fo the use.

25 The inteesting ontibutions of this eseah We tied duing this wok to automate the alibation poess as muh as possible. The setup and measuements of the tagets and the ameas. The automation of the taget loations in the images, and thei subsequent efinement. The automati poess fo balaning the adial lens distotion in the pesene of othe oelated paametes. ACKNOWLEDGEMENT We would like to aknowledge the suppot of the Am Reseah Offie and the Topogaphi Engineeing Cente.