LIDAR와 영상 Data Fusion에 의한 건물 자동추출

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15 Image Processing Image Pyramid Edge Detection Epipolar Image Image Matching LIDAR + Photo Cross correlation Least Squares Epipolar Line Matching Low Level High Level Space Intersection Virtual LIDAR Data Building Extraction 5

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17 Ranging Unit Scanner Control, Monitoring and Recording Units LASER FOOTPRINT DGPS IMU flight directi on swath width scan direction 7

18 A T A T t t A R A R t t t L t L (a) (b) A Linst h θ inst dx across 8

19 dx along 비행방향비행방향비행방향 9

20 f L y x a o a x y a Z L Z Y A X A Z A X L Y A Y L X 10

21 f (X L, Y L, Z L ) (X, Y, Z ) (x, y ) (x 0, y 0 ) r ij R i j R 11

22 P S P L Q P R L 왼쪽사진투영중심 f Q L E L Epipolar Axis E R Q R f R 오른쪽사진투영중심 S 12

23 O O' P P' A P P' y y y 13

24 (r, c ) (x, y ) R N = R B R T R R T R N R N 14

25 R N 15

26 f P = f N Z Z 수치영상 y P 수치영상 y P p P p P x P x P f P Y f P Y X X -f N y N 수직영상 -f N y N 수직영상 x N x N p N p N y 16

27 x y 표정작업전 항공사진 표정작업후 normalized 사진 projective 좌표변환 ( 기하학적좌표변환 ) Affine 좌표변환 에피폴라영상의크기설정 수치영상 normalized 영상 영상재배열 (resampling) (a 1, a 2 ) A A 17

28 L1 L2 a1 a2 Z o1 o2 Y XA A ZA YA X 18

29 Image Profile of a horizontal line First derivative Second derivative (a) (b) 19

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31 ρ ρ ρ ρ = σ LR σ L σ R σ LR L R σ L L σ R R ρ 1 ρ 1 ρ 기준영역 Template column 정합대상영역 Search area column initial point matching start point target point row row 21

32 g L ( x, y) g R ( x, y) g L g R σ L σ R σ LR σ L = σ R = g L = Σn i =1Σ m j =1g L ( x i, y j ) n m g R = Σn i =1Σ m j =1g R ( x i, y j ) n m Σ n i =1Σ m j =1 g L ( ) n m 1 Σ n i =1Σ m j =1 g R ( ) n m 1 x i, y j g L 2 x i, y j g R 2 σ LR = Σn i =1Σ m j =1 g L ( x i, y j ) g L g R ( x i, y j ) g R n m 1 n m 22

33 (x s, y s ) g t g s 23

34 기준영역 Template column 정합대상영역 Search area column initial point target point matching start point row row h 0 h 1 g t (x t, y t )= h 0 + h 1 g s (x s, y s ) + n (x s, y s ) g t (x t, y t ) (x t, y t ) g s (x s, y s ) (x s, y s ) n (x s, y s ) h 0 h 1 X = a 0 + a 1 x s + a 2 y s Y = b 0 + b 1 x s + b 2 y s 24

35 a 0 a 1 a 2 b 0 b 1 b 2 g t = h 0 + h 1 g s [( a 0 + a 1 x s + a 2 y s ), ( b 0 + b 1 x s + b 2 y s )] + n(x z,y s ) g t g s x s y s F = h 0 + h 1 g s [( a 0 + a 1 x s + a 2 y s ), ( b 0 + b 1 x s + b 2 y s )] F F = F 0 + F h 0 + F h 1 + F a 0 + F a 1 + F a 2 + F b 0 + F b 1 + F b 2 = F 0 + dh 0 + g s (X, Y ) 0 dh 1 + h 1 g s (X, Y ) X + h 1 g s(x, Y ) Y (1 + x + y) 0 (1 + x + y) 0 g t (x t, y t ) g s (X, Y )=dh 0 + g s (X, Y ) 0 dh 1 + h 1 G X0 + h 1 (G x x ) 0 + h 1 (G X y) 0 + h 1 G Y0 + h 1 (G Y x ) 0 + h 1 (G Y y) 0 h 1 G X0 = da 0 h 1 (G X x ) 0 = da 1 h 1 (G X y ) 0 = da 2 h 1 G Y0 = db 0 h 1 (G Y x ) 0 = db 1 h 1 (G Y y ) 0 = db 2 25

36 AX = L + V A = 1 g s (X,Y) 1 h 1 G 1 X 0 h 1 G X x 1 0 h 1 G X y 1 0 G 1 Y 0 G Y x 1 0 G Y y g s (X,Y) 2 h 1 G 2 X 0 h 1 G X x 2 0 h 1 G X y 2 G 2 0 Y 0 G Y x 2 0 G Y y g s (X,Y) n h 1 G n X 0 h 1 G X x n 0 h 1 G X y n 0 G n Y 0 G Y x n 0 G Y y n 0 X = dh 0 dh 1 da 0 da 1 da 2 db 0 db 1 db 2 L = g t (x t, y t ) 1 g s (X, Y) 1 g t (x t, y t ) 2 g s (X, Y) 2 g t (x t, y t ) n g s (X, Y) n 3 3 AX = L + V X = ( A T A) 1 AL σ 2 V = T V n m 8 26

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42 (a) 원영상 (b) canny filter 적용결과 (c) threshold 100 으로이진화 (d) thinning 적용최종영상 32

43 (a) 원영상 (b) laplacian filter 적용결과 (c) threshold 100 으로이진화 (d) thinning 적용최종영상 33

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46 pixel original matching point epipolar line matching points edge

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48 (a) original LIDAR data (b) virtual LIDAR data 38

49 (a) original LIDAR data (b) virtual LIDAR data 39

50 (a) Left Photo (C5-11) (b) Right Photo (C5-10) 40

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54 (a) LIDAR 데이터 (b) 건물추출결과 44

55 (a) 가상 LIDAR 데이터 (b) 건물추출결과 45

56 (a) LIDAR 데이터 (b) 건물추출결과 (a) 가상 LIDAR 데이터 (b) 건물추출결과 46

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58 (a) LIDAR 데이터 (b) 건물추출결과 (a) 가상 LIDAR 데이터 (b) 건물추출결과 48

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60 (a) building A (b) building B (c) building C (d) building D (e) building E (f) building F 50

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