INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 6, No 1, 2015

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1 INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 6, No 1, 2015 Copyright by the authors Licensee IPA Under Creative Commons license 3.0 Research article ISSN Evaluation of stereoscopic measurement accuracy for airborne large format digital camera Sreedhar M, Shashivardhan Reddy P, Narender B, Muralikrishnan S Aerial Services & Digital Mapping Area, National Remote Sensing Centre, Hyderabad, India sreedhar_m@nrsc.gov.in ABSTRACT Stereoscopic depth perception plays a vital role in photogrammetry, as it enables the formation of a 3D stereo model by viewing a pair of overlapping photographs. The stereo model can then be studied, measured and mapped. In this study, the stereoscopic measurements of images from UltracamD digital camera, acquired at 10cm GSD are investigated by carrying out repetitive measurements of various geometric features by an experienced photogrammetrist. The features selected for measurements are having different contrast like dark tonal variations in shadows and bright tonal variations with bright background. The measurements are validated with that of ground values to evaluate the achievable horizontal and vertical accuracy. Traditional standards for map accuracy give the horizontal accuracy as 0.25mm of map scale and vertical accuracy in terms of contour interval. The study shows the images acquired with high radiometry and color information helps to measure the features in low contrast conditions with reasonable good accuracy. In this study the root mean square (RMSE) achieved in different contrast conditions and for different geometrical features are 7.7cm in horizontal and 12.5cm in vertical. The results shows, by using 10cm GSD color data, geospatial information at 1:500 scale can be prepared with 0.5 m contour interval. Keywords: Stereo measurement, UltracamD camera, accuracy 1. Introduction Aerial imaging till last decade is dominated by analog film cameras. Since the analog and analytical photogrammetry has transformed into digital domain, analog film needs to be transformed into digital domain by precession scanners. However with the advent of aerial digital cameras, intermediate process of scanning is eliminated in digital photogrammetric processing. Moreover digital cameras yields images immediately after flying without the need to wait for other processes required for film based cameras. The most important advantage is the ability to dramatically increase the forward overlaps in photogrammetric surveys without any additional flying cost and producing a much higher level of automation in photogrammetric data analysis. Digital Photogrammetric Cameras are classified into two categories viz. line cameras and large format frame cameras. The large format digital aerial cameras are now playing a significant role in the field of digital airborne imaging (Gruber et al., 2008). The geometric model of the sensing system should be determined to any block of images used for a high precision measurement purposes in photogrammetry (Cramer, 2005). The geometric potential of the digital cameras will affect the evaluation of the photogrammetric models (smith et al., 2005). The performance of digital aerial cameras has recently been investigated by several research groups (Jacobsen, 2011), (Haala et al., 2010), (Spreckels et al., 2010), (Höhle, 2009 a,b) and Honkavaara etal., (2006). Submitted on May 2015 published on August

2 The use of digital imagery in large scale mapping applications and GIS requires precise measurement of 3D information. The 3D stereoviewing of images, improves the interpretation and measurement of imagery of almost all types of terrain (petrie, 2001). In this regard, stereoscopic depth perception plays a vital role in photogrammetry as it enables the formation of a 3D stereomodel by viewing a pair of overlapping photographs. Perceiving depth by stereoscopy is a basic requirement in photogrammetric 3D measurement & accurate geospatial data collection (Jieshan, 2006). The important factor for stereovision is having good binocular vision wherein two slightly different images from two eyes are successfully combined into one three dimensional image in the brain. Visual acuity, which is measure of the ability to resolve fine detail, is one of the important factor governing the depth perception. Normal visual acuity is 20/20 (Wattie, 2004). In the present study images acquired from Vexcel UltracamD Large Format Digital Camera are used. The sensor unit consists of eight independent cameras called cones. Four of the cones create a panchromatic image of size 11,500 pixels by 7,500 pixels. Color is simultaneously recorded at a frame size of 4k by 2.7 k pixels for red, green, blue and near infrared (smith et al., 2005). The 12bit dynamic range for every channel gives much more information to be derived from shadowed areas as compared to 8bit scanned imagery. In this paper, an attempt has been made to evaluate the achievable geometric accuracy of Ultracam D digital camera images in all contrast conditions. Repetitive measurements of the features in planimetry and vertical are carried out by an experienced photogrammetrist and the results are validated with ground measurements. 2. Study area and Objective The study area covers part of Hyderabad, India. The images at 10cm GSD are acquired using Large Format Digital Camera (LFDC) UltrcamD flown during March The flying height of the aircraft is 1100m above terrain level. The objective of the study is: 1. To define the map accuracy standards and achievable accuracy in horizontal and vertical measurements. 2. To carry out statistical tests like mean absolute percentage, chisquare test, standard and ttests for observed data with field measurements. 3. Validation of stereoscopic (horizontal and vertical) measurements with that of field measurements. 3. Methodology The methodology adopted in the present study is shown in the flow chart (Figure 1). Photogrammetric adjustment of digital aerial images is carried out using the Onboard kinematic GPS (KGPS) and Inertial Measurement Unit (IMU) data. The KGPS data is differentially corrected with ground based GPS receiver that is operated simultaneously at the time of data acquisition. Homologous points (tie points) are added to remove the Yparallax. The Root Mean Square Error (RMSE) after the photogrammetric adjustment of all the images is 0.2 pixels. Horizontal and vertical measurements of different geometrical features are measured on the ground with steel tape having a precision of 1mm. It is ensured that ground measurements taken with steel tape are free from s and they represent the true values. A total of 20 features (point 1 to point 20) are selected for horizontal measurements and total of 12 features 12

3 (point 1a to point 12a) are selected for vertical measurements. The features selected for measurements are chosen such that they fall in different contrast conditions. For example the selected features have bright tonal variation with bright background, dark tonal features in shadows and shallow depth features having uniform contrast with varying depth and dimension. Figure 2a&2b and Figure 3a&3b shows the sample of features that are selected for measurements. Figure 1: Methodology for evaluation of stereoscopic measurements. Figure 2a: (point 5) Figure 2b: (point 7) Figure 2a&2b: Ground features selected for horizontal measurements Tests 1 to test 5 are the repetitive measurements (horizontal & vertical) of features carried out by a photogrammetrist. Statistical analysis has been carried out to arrive at the achievable horizontal and vertical measurements. The result of horizontal measurements with ground measurements is shown in table 1 13

4 Figure 3a: (point 8a) Figure 3b: (Point 12a) Figure 3a&3b: Ground features selected for vertical measurements Table 1: Error analysis for horizontal measurements. S.NO Actual Length L(m) Test1 Test2 Test3 Test4 Test5 L1 L2 L3 L4 L5 Mean L Std Dev The results of vertical measurements with ground values are given in table 2. 14

5 poin t no S.NO Evaluation of stereoscopic measurement accuracy for airborne large format digital camera Actual Height H(m) Table 2: Error analysis for vertical measurements Test1 Test2 Test3 Test4 Test5 L1 L2 L3 L4 L5 1a a a a Mean L Std Dev a a a a a a a a Chi Square analysis for horizontal and vertical measurements is given in table 3&4. Actual Length L(m) Test1 Table 3: Chi Square analysis for horizontal measurements. Test1 Test2 Test2 Test3 Test3 Test4 Test4 Test5 Test5 Mean Chi Square % % % % % % % % % % % % % % % % % % % 0.3 3% % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % % %

6 Table 4: Chi Square analysis for vertical measurements. Paired ttest (two tailed) analysis is carried out to check if the observations and the actual values are within the accepted level of significance. The test for horizontal and vertical measurements is given in Table 5 & 6. The standard for horizontal and vertical measurements is given in table 7. Table 5: Paired ttest (two tailed) for horizontal measurements. Test 1 Test 2 Test 3 Test 4 Test 5 t Statistics P(T<=t) onetail t Critical onetail P(T<=t) twotail t Critical twotail Table 6: Paired ttest (two tailed) for vertical measurements Test 1 Test 2 Test 3 Test 4 Test 5 t Statistics P(T<=t) onetail Table t Critical onetail : P(T<=t) twotail t Critical twotail Standard for horizontal and vertical measurements. Standard Horizontal Error(cm) Standard Vertical Error(cm) Test 1 Test 2 Test 3 Test 4 Test The Normal distribution, which shows the distribution of around mean for both the measurements, is shown in Figure 4a&4b. 16

7 Figure: 4a Figure: 4b. Figure: 4a and 4b Normal distribution curve for Horizontal and vertical. 4. Results and discussion From table1 of horizontal measurements maximum of 13.2 cm is observed at point no.20 where feature is bright with white back ground and at point no.7 the is 11cm, where feature is dark with dark back ground. Table 3 & 4 shows the chisquare analysis for horizontal and vertical measurements to test the goodness of fit and tested if the deviation between the observed value and the actual value at each point is significant or not. In chisquare test the tabulated value is at 5% level of significance, as the calculated value at each individual point is less than the tabulated value of at four degrees of freedom the null hypothesis is accepted. This test shows that the stereo measurements carried for horizontal and vertical does not have any blunders. Twotailed paired t test is done at mean level to find if the average difference between the actual and observed value is equal to zero (i.e., statistically equal). For heights, the null hypothesis is rejected as the average difference between the actual and observed value is not equal to zero (i.e., statistically not equal). Hence, to find, if the noise is test specific or spread across tests, paired t test is done for each test ( table 6). It is found that test5 could not qualify the criteria while other measurements are passed. For lengths, the null hypothesis is accepted as the average difference between the actual and observed value is equal to zero. From table 6, it can be referred that test4 could not qualify. It can be inferred that though only one test has failed the criteria test for heights and lengths, but at the mean level, the hypothesis got rejected for heights and accepted for lengths, due to stronger correlation of values in lengths than heights. From the standard vertical (table 7) of stereotests, it can be inferred that the most accurate vertical and horizontal measurement at 95% confidence interval (2σ) is 32 cm and 15cm respectively. It is observed that the measurements follow normal distribution and the s are random in nature (Figure 4a and 4b). The Root Mean Square Error (RMSE) is 7.7cms and 12.5 cms for horizontal and vertical measurements. The mean is 2.2cm and 5.12cm for horizontal and vertical measurements. The shape of normal distribution curve is bell shaped and is narrow which indicates a close proximity of the s to each other and the mean.. From table 2 of analysis for vertical measurements standard varies from 9.3cm to 21cm. Maximum in vertical measurement is observed at point no.1a where the feature is located on ground having gentle slope. All the tests either overestimated or underestimated the vertical measurements with the true value. Judgment of depth of a point depends on the surrounding area and the contrast of the feature. 17

8 5. Conclusions The important factors influencing the accuracy for extraction of information from stereoimages are investigated. This study helps in deriving map accuracy standards, achievable accuracy in measurements and factors influencing the s in stereoscopic measurements at 10cms GSD. The root mean square in horizontal and vertical measurements for all the samples in different contrast conditions are 7.7cms and 12.5cms. The measurement follows the gaussian distribution and statistically stereoscopic measurements have smaller range and smaller variation and are centralized. As per ASPRS standard for class1 map at 1:500 scale, the limiting planimetric is 12.5cm and to generate 0.5m contour interval the vertical accuracy required is cm. In this study the Root Mean Square Error (RMSE) achieved in planimetry and height is 7.7cm and 12.5cm which are well within the accuracy limits of 1:500 scale mapping. Acknowledgements The authors express their sincere thanks to Sri. P. Srinivasulu, General Manager, Aerial Services & Digital Mapping Area (AS&DMA) and Dr. V.K. Dhadwal, for their support and encouragement during the study. 6. References 1. Cramer M., (2005), Digital Airborne CamerasStatus and Future. ISPRS Hannover Workshop on High resolution Earth imaging for geospatial information Proceedings, 36(1), PP Gruber, M., Ponticelli, M., Berngger, S., Leberl, F.,(2008), Ultra CamX, the Large Format Digital Aerial Camera System by Vexcel Imaging /Microsoft, Intl. Archives for Photogrammetry, Remote Sensing & Spatial Information Sciences, vol. XXXVII, no. B1, pp Haala, N., Hastedt, H., Wolf, K., Ressl, C., Baltrusch, S., (2010), Digital Photogrammetric Camera Evaluation Generation of Digital Elevation Models, PFG 2/2010, pp Höhle, J., (2009a), DEM Generation Using a Digital Large Format Frame Camera, Photogrammetric Engineering & Remote Sensing (PE&RS), 75(1), pp Höhle, I.,(2009b), Updating of the Danish Elevation Model by means of photogrammetric methods, National Survey and CadastreDenmark, technical report number Honkavaara, E; Ahokas, E; Hyypp, J., Jaakkola, J., Kaartinen, H., Kuittinen, R., Markelin, L., Nurminen, K., Geometric test field calibration of digital photogrammetric sensors, ISPRS Journal of photogrammetry and Remote Sensing, 60(6), pp Jacobsen, K., (2011), Geometric Property of Large Format Digital Camera DMC II

9 8. Jie Shan., ChiungShiuan Fu., Bin Li., James Bethel., Jeffrey Kretsch., and Edward Mikhail., 2006, Principles and Evaluation of Autostereoscopic Photogrammetric Measurement Photogrammetric Engineering & Remote Sensing, 72(4), pp Petrie, G., (2001), 3D stereo viewing of Digital Imagery: Is AutoStereoscopy the future for 3d?, Geoinformatics, 4(10), pp Spreckels, V., Syrek, L., Schlienkamp, A., (2010), DGPF Project: Evaluation of Digital Photogrammetric Camera Systems Stereoplotting. 11. Smith, M.J., Qtaishat, K.S., Park, D.W.G., jamieson, A., (2005), Initial results from the VexcelUltraCam digital aerial camera. In: 12. Wattie, J., (2004), Stereoscopic Vision Elementary Binocular Physiology. 19