AUTOMATIC SATELLITE IMAGE REGISTRATION BY COMBINATION OF STEREO MATCHING AND RANDOM SAMPLE CONSENSUS

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1 AUTOATIC SATELLITE IAGE REGISTRATION BY COBINATION OF STEREO ATCHING AND RANDO SAPLE CONSENSUS Taejung Ki* Yong-Jo I** *Satellite Technology Research Center Korea Advanced Institute of Science and Technology Kusung-Dong, Yusung, Taejon, Korea Eail: **Satellite Technology Research Center Korea Advanced Institute of Science and Technology Kusung-Dong, Yusung, Taejon, Korea Eail: KEY WORDS: Autoatic registration, precision correction, RANSAC, stereo atching. ABSTRACT: In this paper, we propose a new algorith for autoated iage registration or precise correction of satellite iages. We assue that ground control points used previously are stored within the syste. The algorith first applies atching between the GCP chips stored and a new iage to be registered and creates new control points. An autoated stereo atching based on noralized cross correlation will be used for atching. Then the algorith applies Rando Saple Consensus to discriinate false atches fro being considered for odeling. We believe that robust estiation schee is iportant for autoated iage registration. We carried out experients with SPOT iages over three test sites. Through stereo atching, a nuber of control points were generated. The RANSAC was applied to the control points. All outliers were correctly identified for all three test sites and apping functions estiated without outliers. The accuracy of estiation was coparable to that of estiation with control points generated all by anual easureents. The results support that our algorith can be used for robust autoated registration. 1. INTRODUCTION In order to utilize reotely sensed iages in geographic applications, it is necessary to relate iage coordinates to a reference coordinate syste (datu), to a ap, or to a reference iage. This process is referred to as iage registration. After registration, we ay rearrange the pixel values of the raw iage so that the grids of new iage align with reference coordinate syste. This process is called as geoetric correction. In processing satellite iages, there are two kinds of geoetric correction. One is systeatic correction and the other is precision correction. Systeatic correction is to rearrange (or

2 resaple) the iage with ancillary inforation given fro the satellite on-board sensors and without ground control points whereas precision correction uses ground control points. Precision correction offers higher accuracy than systeatic one but does require significant huan operation. In this paper, we propose a new ethodology for autoated iage registration with ground control points or precision correction of satellite iages. As entioned, iage registration or precision correction requires ground control points (GCPs), a point whose iage coordinates and whose reference coordinates are known. Traditionally they have been generated by huan operators. Substantial huan involveents are required for the task and reduction of huan involveents becae an iportant issue. This paper will address a new algorith for reducing such huan involveent in iage registration by autoatically generating ground control points. We assue that ground control points used previously are stored within the syste and create a new ground control points for a new iage to be registered by stereo atching. There are any previous publications dealt with the autoation in this step, in particular for the preparation of error-free ground control points [1-3]. It is however iportant to notice that while devising error-free stereo atching schee is very difficult, a siple robust estiation can help the robustness of autoated iage registration to a great deal. We accordingly will use the Rando Saple Consensus (RANSAC) schee[4] in order to filter out any isatches fro stereo atching and achieve reliable autoation in iage registration. The detailed explanation is given in the next section. 2. AUTOATIC IAGE REGISTRATION ETHOD Our algorith works in two steps: The first one is the autoated generation of control points using stereo atching. The second one is the robust estiation of apping functions using control points filtered out through the RANSAC. Although the algorith in this paper can be extended to other type of iages, we liit our discussion here to satellite iages. We assue that satellite iages will possess ancillary data, i.e., the inforation on approxiate coordinates of four corners, tilt (or incidence) angle and scene orientation angle. We further assue that we have a-priory knowledge on the approxiate error boundaries of the ancillary data. For the generation of control points, we first define the region of interest (ROI) for a new iage to be registered (hereby iage). A ROI is defined by extending scene boundaries defined in ancillary data of a iage to allow for errors in the. Then GCP chips within the ROI is searched for. Then atching proceeds between the iage and GCP chips. Results of atching constitute new GCPs of the iage. For stereo atching, we use the noralized cross correlation as a easure to deterine the correspondence. In this step, the ancillary data of the iage and GCP chips are utilized. The size

3 of window is set adaptively according to the scale difference between the GCP chips (reference) and the iage. The scale difference is ainly due to differences in ground sapling distances and different incidence angles. A proper scale factor ust be introduced to take this into account. Different scene orientation angles between the reference and iage (or window) iply that the ground footprints of the reference and windows do not coincide even though the center points of reference and windows are perfectly aligned. This effect can be eased by rotating the window to the aount of orientation difference. Through this procedure, we can generate GCPs autoatically. The second step is the robust estiation of a caera odel for the iage. This can be done by reoving isatches by RANSAC and estiating caera odels with control points reained. The Rando Saple Consensus (RANSAC) proposed by [4] is a powerful and robust estiator in the presence of outliers (or isatches). We can apply the RANSAC without the prior knowledge of error distributions. As long as we can tell the boundaries between inliers (or true atches) and outliers the RANSAC works. In our case of autoatic registration, we can distinguish the inliers and outliers by the aount of caera odeling error. When we establish a caera odel and a control point deviates fro the odel by ore than, say, three pixels, we can tell the point is not supporting the odel. The RANSAC works by estiating a odel with iniu required nuber of control points selected randoly and checking whether other control points support the odel. It repeats these procedures for a certain nuber of ties and chooses the best odel that has the largest supports. After that, it reestiates the odel using those control points used for the best odel and other supporting control points. In fact, robust estiation is one of the key eleents in any coputer vision probles. It is soewhat strange that for autoated registration this schee has not been popular. Here, we will show that robust estiation can work for our purpose. Aong several apping functions (or caera odels) available for satellite iages, we will use the direct linear transforation odel (DLT) by Gupta and Hartley[5]. This algorith is expressed in a atrix for and easier to handle. However, the algorith described in this paper can work with other caera odels. Estiating the apping function of the DLT odel is finding coefficients of ij using control points C R ; X, Y, Z t arg et, t arget ref ref ref. wct Rt arg w arget et X Y Z 1 ref ref ref

4 3. RESULTS AND DISCUSSIONS Three test sites were chosen for deonstration of our approach. For each test site, a stereo pair of SPOT iages and GPS surveyed GCPs were prepared. Table 1 suarizes the characteristics of stereo pairs and GCPs. Table 1. Suary of test scenes and test control points Test Site Taejon Boryung Junju Scene Acquisition L: Oct. 14, 1997 L: arch 1, 1997 L: Oct. 14, 1997 Date R: Nov. 15, 1997 R: Nov. 15, 1997 R: Nov. 15, 1997 Incidence Angle L: 29.7 L: L: 29.7 R: 4.9 R: 0.5 R: 4.9 Scene Orientation L: 13.7 L: 8.1 L: 13.7 angle R: 11.3 R: 10.9 R: 11.3 No. of GCPs For each test site, the left iage was used to create GCP chips and the right iage as a iage to be registered. Sall iage windows were defined on GCPs over the left iage and were stored in the syste as GCP chips. The ancillary data of the right iages were used to define a ROI and to search for GCP chips within the ROI. Since the GPS surveyed GCPs were all lying within the stereo coverage, all GCP chips created were searched for. Autoated atching was carried out. For each GCP chip, a point with highest noralized cross correlation (NCC) value was chosen as a correspondence. The search range was set as 2ks (or 200 pixels). Table 2 suarizes the result of autoated stereo atching for the three test sites. Table 2. Results of autoated stereo atching. Each result shows the nuber of true atches versus the nuber of false atches. Test site Taejon Boryung Junju NCC > < NCC < 0.8 NCC < : 0 7 : 7 NA 5 : 0 9 : 3 2 : 1 7 : 0 2 : 2 0 : 5 Total 14 : 7 16 : 4 9 : 7 atch results were classified by their highest NCC values. Within each class the nuber of true atches versus the nuber of false atches are shown. If a atch point did not deviate fro the anually easured correspondence by ore than three pixels, it was classified as a true atch. For Taejon, autoated atching created 14 true atches and 7 false atches in total. In this case, if the NCC value

5 was higher than 0.8, there was no false atches. If the NCC value lied between 0.6 and 0.8, there were 7 false atches aong 14 atch points. For the other two sites, test results can be read siilarly. Figure 1 shows a few exaples of true and false atches for Taejon test site. It is notable that there are quite different brightness patterns between the GCP chips and the right iage patch even for the true atches. Aong the atch results, the RANSAC selected randoly eight points for estiation and others for checking supports. For experients, iteration nuber was set to 2000 for all three, although there are eans to autoate such iteration nuber. The distance of three pixels was used again to decide whether a CP was supporting the estiation or not. The best odel, which had the largest supports, was re-estiated with all supporting GCPs. Table 3 suarizes the estiation of through the RANSAC. For coparison, was also estiated using all anually easured control points.

6 CP chips Exaples of CP chips Exaples of True atch False atch Figure 1. A few exaples of true and false atches for Taejon test site. Table 3. The estiation of through the RANSAC Test Area Taejon Boryung Junju odeling with the RANSAC No. of points used for odeling No. of outlier detected odeling error (RS) 0.70 pixels 0.79 pixels 0.90 pixels odeling with the true CPs No. of points used for odeling odeling error (RS) 0.41 pixels 0.60 pixels 0.44 pixels The table 3 shows that RANSAC has successfully detected all outliers. For Junju site, there were several odels that had the largest supporting nuber of one. This abiguity was because the nuber of inliers was only one ore than the iniu nuber of points required for odeling. Outliers were by accident

7 lying closely to the estiation. This abiguity was resolved correctly by taking the average supporting distance into account. This phenoenon indicates the liitation of the RANSAC or our approach. We need the nuber of inliers ore than, say, nine for robust estiation of. The odeling accuracy of fro the RANSAC was copared to the odeling accuracy of estiated by true GCPs. The accuracy of the forer was lower than but coparable to that of the latter. For all three sites, it was better than one pixel. Note that the GCPs used for the latter were error-free whereas the GCPs, inliers as well as outliers, used for the forer contained errors. 4. CONCLUSIONS This paper proposed a ethod to solve the iportant proble of autoated iage registration. We ephasized the role of robust estiation in autoated registration. We ed satellite iages, which norally possessed ancillary data. We devised a siple but efficient stereo atching algorith to produce control points autoatically. We then used the RANSAC to estiate apping functions in the presence of outliers. The experients supported that our algorith worked well. As earlier results in other applications, this paper provides the successful application of the RANSAC in autoated iage registration and in autoated precision correction of satellite iages REFERENCES [1] J. Ton and A. K. Jain, Registering Landsat iages by point atching, IEEE Trans. Geoscience and Reote Sensing, vol. 27, no. 5, pp , Sept., 1989 [2] A. D. Ventura, A. Rapini, and R. Schettini, 1990, Iage registration by recognition of corresponding structures, IEEE Trans. Geoscience and Reote Sensing, vol. 28, no. 3, pp , ay, 1990 [3] V. Govindu and C. Shekhar, Alignent using distributions of local geoetric properties, IEEE Trans. Pattern Analysis and achine Intelligence, 21(10): , Oct [4]. A. Fischler and R. C. Bolles, Rando Saple Consensus: A paradig for odel fitting with applications to iage analysis and autoated cartography, Counications of the Assoc. Cop. ach., vol. 24, no. 6, pp , June 1981 [5] R. Gupta and R. Hartley, Linear pushbroo caeras, IEEE Trans. Pattern Analysis and achine Intelligence, vol. 19, no. 9, pp , Sept. 1997

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