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1 GIS 389 Vol.2, No., Spring 200 Iranian Remote Sensing & GIS * /4/ : 388//4 :. SIFT... Harris SIFT SIFT. Harris SIFT : : * : am.sedaghat@gmail.com

2 ( ) ). ( (Gruen, 987) LSM 3 (Kern and Pattichis, 2007) (Keller and Averbuch, 2006) Implicit Similarity LSM. 0/02 ).(Remondino et al., 2008) (. ) ( 32.(Zitova and Flusser, 2003) ) (. Schmid et al., 2000; Jing and ).(Allinson, Image Registration 2. Resampling 3. Mutual Information - Zitova and ).(Flusser, ( ) I2 ( ) I. 2. Zitova and Flusser, 2003; Brown, 992; ).(Goshtasby, 2005 Wong and ).(Clausi, 2007 ) ( ) ( ( ) Zitova and Flusser, 2003; Wong and ).(Clausi,

3 (Harris and Stephens, 988) Harris. SIFT Yu (Yu et al., 2008) SIFT. SIFT Harris. SIFT. Harris-SIFT. RANdom Sample Consensus 2. Feature Vector 3. Moment Invariants 4. Scale Invariant Feature Transform 5. Automatic Registration of Remote Sensing Images 6. Phase Congruency. Fischler ) RANSAC. (and Bolles, 98 2 ( ). 3 (Belongie et al., 2002) Shape Context (Mindru et 4. (Lowe, 2004) SIFT al., 2004).(Wong and Clausi, 2007). 6 5 ARRSI MDSAC RANSAC Wen.(Wong and Clausi, 2007). Wen et al., ).(2008 Yu Yu et ).(al., 2008 SIFT 389 3

/ k DoG..( ). ) DoG 8 ( 9 DoG 9 DoG ( ). 3 Lowe 32. 5 DoG 6 26 3D Quadratic. DoG ) 4 (. (T c ). 6. Difference of Gaussian 2. Octave 3. Convolution 4.

4 / k DoG..( ). ) DoG 8 ( 9 DoG 9 DoG ( ). 3 Lowe DoG D Quadratic. DoG ) 4 (. (T c ). 6. Difference of Gaussian 2. Octave 3. Convolution 4. Ratio Between the Principal Curvatures.. SIFT -2 SIFT --2 SIFT Lowe.(Lowe, 2004). SIFT DoG 2.( ) () 0 k 0 k 2 0 k 3 0 k 4 0 k 5 0 (2) k 3 0 k 4 0 k 5 0 k 6 0 k 7 0 k 8 0 IKONOS DoG. 3.( ) 389 4

5 .. 4 6=24 DoG 4 5= =36 DoG. 26. Ledwich and Williams, 2004; ).(Tamimia et al., 2006 Yu. SIFT (Yu et al., 2008).. (T r ) (2004) Lowe.. 0 0/03 T r T c. SIFT (4 4 8=28). Lowe,.. SIFT Mikolajczyk.2004 SIFT Shape Context.(Mikolajczyk and Schmid, 2005) Ke. PCA Sulthankar.(Ke and Sukthankar, 2004) Li et ) : al., 2009; Wang et al., 2008; Li and Ma, 2009;.(Heikkil et al., 2009 SIFT -2-2 SIFT SIFT 389 5

6 (3. Harris Harris-SIFT.2 SIFT Harris-SIFT. Harris Harris-. SIFT SPOT 4 Landsat ETM SIFT.(Cheng et al., 2008) SIFT. 4 Harris DoG.... SIFT. -3 Harris-SIFT SIFT 2. ( : (2 Harris-SIFT 389 6

7 . Quickbird 0/67. IKONOS 0/ {/ 0 670,/,/ 40 2}. IRS SPOT Characteristic Scale Harris-SIFT ---3 SIFT.. SIFT.. Sn(n 2,, 3) Bilinear

8 ... : : ( Schmid et al., ).( (2 ) Harris : (2.(Schmid et al., 2000).(Zhu et al., 2006-b) ) ( 5.(3 ) E i 2 i P log P i (3) i P i..(zhu et al., 2006-a) Zitova ) Harris and ) Harris.(and Flusser, 2003 (Stephens, 988 Schmid (Schmid et al., 2000) ) ) ( ( Foerstner and ) Foerstner (Gulch, 987. Harris : I2 x IxI y H G(x,y, w ) 2 () I I I y x y I y x I x G(x,y, w ) y M H Harris. : MH Det(H) Trace 2(H) (2) Trace (H) Det (H) H a. 0/04 Harris (2 ) 8 Harris

9 Nf _Cell i E _Cell i W E.. 0/5 5 Harris. n_cell i... N SIFT...(Zhu et al., 2006-a).. (N). ( N l ). Harris.. (n_cell i ) (4). (N l ) : n_cell i (4) n_cell i we E_Cell i ( w E) Nf _Cell i Nl E_Celli Nf _Celli ( (. ( :

10 SIFT (8 4 4)... SIFT.(Lowe, 2004) SIFT ( -5 ) ( -5 ).. R 5 R...( -3 ) / ).(. 3.( 3 ) SIFT (4 )

11 SIFT (.5. ( Lowe. T ED 0/ =04. 5 ) 2/5. (

12 ... RMSE ( 0) ) (. Yu et al., 2008; Hong and ).(Zhang, Root Mean Square Error Pi P. qj Q. p i p i q j q j. P. Navy. (2006)... (RMSE). RMSE ( ).. RMSE

13 ). (.... ) (....(Hong and Zhang, 2008) Yu et al., 2008; Hong and ). (Zhang, Bilinear. -4 SIFT Harris-SIFT. Matlab 3.. ( ) ( ) ( ) Hangzhou Multispectral Multispectral SPOT4 Landsat TM Halifax Panchromatic Multispectral SPOT 5 Landsat ETM Panchromatic Panchromatic IRS-C SPOT / Panchromatic Panchromatic IKONOS IRS-P

14 ... (Gilles, 998) Gilles (LSM) 200~ RMSE Check 2. RMSE Check. 7 q p q q q p.... Landsat SPOT4 (Yu et al., 2008) Yu TM. SIFT.. 2CHz --4. RMSE Proj

. SIFT Harris-SIFT. -2-4 N 4000 00. 5. 5 RMSE. SIFT. ( SIFT Demo Program) Lowe Yu 0/5 RMSE 0/5 0/5 2.. SIFT demo Program (Vession 4, 2005) http://www.

15 . SIFT Harris-SIFT N RMSE. SIFT. ( SIFT Demo Program) Lowe Yu 0/5 RMSE 0/5 0/5 2.. SIFT demo Program (Vession 4, 2005) V4. zip RMSE a. RMSE Check. RMSE Reg =RMSE a -).(RMSE Check.7 : : (. :RMSE Reg (2. RMSE a RMSE Reg. : (

16 2 25 SIFT Yu ) SIFT (Yu et al., 2008)... Harris-SIFT 65 (8 ) Harris-SIFT. SIFT SIFT Harris-SIFT SIFT. Harris- RMSE. SIFT 2 SIFT 58 Landsat TM 67 Landsat ETM IKONOS. SIFT. 2 ( ) RMSE RMSE Reg 0/2852 0/5249 0/9243 0/6430 Harris-SIFT SIFT.2 RMSE Check RMSE Proj 0/4527 0/984 0/7459 /037 0 / / / /8766 ( ) Harris-SIFT SIFT Harris-SIFT SIFT N GM Harris-SIFT SIFT SPOT4 Landsat TM SPOT 5 Landsat ETM IRS-C SPOT 4 IKONOS 40. LSM Gilles :. : Harris-SIFT RMSE :2. RMSE :RMSE Proj RMSE :RMSE Check. :RMSE Reg 389 6

17 Landsat TM SPOT4..8 SIFT... Harris-SIFT 9.. RMSE Reg 2 RMSE Check. RMSE Reg Harris-SIFT 0/ Harris-SIFT

18 IRS-P6 IKONOS :.9-5 Harris-SIFT SIFT. SIFT. Harris.. Harris-SIFT.. ENVI V4.3, ITT, 2006, SIFT. SIFT 4 SIFT SIFT ) SIFT ( SIFT V4/3 ENVI. (ITT)

19 Fischler, M., Bolles, R., 98, Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography, Commun. ACM, Vol. 24, No. 6, pp Forstner, W., Gulch, A., 987, A Fast Operator for Detection and Precise Location of Distinct Points, Corners and Centres of Circular Features, In Intercommission Conference on Fast Processing of Photogrammetric Data, Interlaken, Switzerland. Gilles, S., 998, Robust Description and Matching of Images, Ph.D. thesis, University of Oxford. Goshtasby, A., 2005, 2-D and 3-D Image Registration for Medical, Remote Sensing and Industrial Applications, Wiley- Interscience, New York. Gruen, A., 987, Adaptive Least Square Correlation: A Powerful Image Matching Technique, South African J. Photogrammetry, Remote Sens. Cart., Vol. 4, No. 3, pp Harris, C. and Stephens, M., 988, A Combined Corner and Edge Detector, In Alvey Vision Conference, UK. Heikkil, M., Pietikainena, M., Schmid, C., 2009, Description of Interest Regions with Local Binary Patterns, Pattern Recognition, Vol. 42, pp Hong, G., Zhang, Y., 2008, Wavelet-Based Image Registration Technique for High- Resolution Remote Sensing Images, Computers & Geosciences, Vol. 34, pp Gilles. SIFT. -6 Yu Yu et al., ). ( Belongie, S., Malik, J., Puzicha, J., 2002, Shape Matching and Object Recognition Using Shape Contexts, IEEE Trans. Pattern Anal. Mach. Intell, Vol. 24, No. 4, pp Brown, L.G., 992, A Survey of Image Registration Techniques, ACM Computing, Vol. 24, pp Cheng, L., Gong, J., Yang, X., Fan, C., Han, P., 2008, Robust Affine Invariant Feature Extraction for Image Matching, IEEE Geosci. Remote Sens. Lett., Vol. 5, No. 2, pp

20 Ke, Y., Sukthankar, R., 2004, PCA-SIFT: A More Distinctive Representation for Local Image Descriptors, Proc. Conf. Computer Vision and Pattern Recognition, Washington, USA, pp Keller, Y., Averbuch, A., 2006, Multisensor Image Registration via Implicit Similarity, IEEE Trans. Pattern Anal. Mach. Intell., Vol. 8, No. 5, pp Kern, J.P., Pattichis, M.S., 2007, Robust Multispectral Image Registration using Mutual-Information Models, IEEE Trans. Geosci. Remote Sens., Vol. 45, No. 5, pp Ledwich, L., Williams, S., 2004, Reduced SIFT Features for Image Retrieval and Indoor Localization, in: Australasian Conf. on Robotics and Automation, Canberra. Li, C., Ma, L., 2009, A New Framework for Feature Descriptor Based on SIFT, Pattern Recognition Letters, Vol. 30, pp Li, J., Allinson, N.M., 2008, A Comprehensive Review of Current Local Features for Computer Vision, Neurocomputing, Vol. 7, pp Li, Q., Wang, G., Liu, J., Chen, S., 2009, Robust Scale-Invariant Feature Matching for Remote Sensing Image Registration, IEEE Geosci. Remote Sens. Lett., Vol. 6, No. 2, pp Lowe D., 2004, Distinctive Image Features from Scale Invariant Keypoints, Int. J. Comput. Vis., Vol. 60, pp Mikolajczyk, K., Schmid, C., 2005, A Performance Evaluation of Local Descriptors, IEEE Trans. Pattern Anal. Mach. Intell, Vol. 27, No. 0, pp Mindru F., Tuytelaars T., Van Gool L., Moons T., 2004, Moment Invariants for Recognition under Changing Viewpoint and Illumination, Comput. Vis. Image Underst, Vol. 94, pp Navy, P., Page, V., Grandchamp, E., Desachy, J., 2006, Matching Two Clusters of Points Extracted from Satellite Images, Pattern Recognition Letters, Vol. 27 pp Remondino, F., Gruen, S.F., Zhang, L., 2008, Turning Images into 3-D Models, IEEE Signal Processing Magazine, pp Schmid, C., Mohr, R., Bauckhage, C., 2000, Evaluation of Interest Point Detectors, Int. J. Comput. Vis., Vol. 37, No. 2, pp Tamimia, H., Andreasson, H., Treptow, A., Duckett, T., and Zell, A., 2006, Localization of Mobile Robots with Omnidirectional Vision using Particle Filter and Iterative SIFT, Robotics and Autonomous Systems, Vol. 54, pp Wang, X., Fu, W., Wang, X., 2008, Optimized SIFT Image Matching Algorithm, Proceedings of the IEEE International Conference on Automation and Logistics Qingdao, China. Wen, G. J., Lv, J. J., Yu, W. X., 2008, A High- Performance Feature-Matching Method for Image Registration by Combining Spatial and Similarity Information, IEEE Trans. Geosci. Remote Sens., Vol. 46, No. 4, pp

21 Wong, A., Clausi, D. A., 2007, ARRSI: Automatic Registration of Remote- Sensing Images, IEEE Trans. Geosci. Remote Sens, Vol. 45, No. 5, pp Yu, L., Zhang, D., Holden, E. J., 2008, A Fast and Fully Automatic Registration Approach Based on Point Features for Multi-Source Remote-Sensing Images, Computers & Geosciences, Vol. 34, pp Zhu, Q., Wu, B., Xu, Z. X., 2006-a, Seed Point Selection Method for Triangle Constrained Image Matching Propagation, IEEE Geosci. Remote Sens. Lett., Vol. 3, No. 2, pp , Zhu, Q. Wu, W. Wan, N. Xu, X., Tian, Y.X., 2006-b, An Interest Point Detect Method to Stereo Images with Good Repeatability and Information Content, Int. J of Acta Electron. Sin, Vol. 34, No. 2, pp Zitova, B. and Flusser, J., 2003, Image Registration Methods: A Survey, Image and Vision Computing, Vol. 2, pp

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