bundle block adjustment with 3d natural cubic splines
bundle block adjustment with 3d natural cubic splines bundle block adjustment with 3d natural cubic splines
Figure 5.2: Six image blockParameter X c [m] Y c [m] Z c [m] ω [deg] ϕ [deg] κ [deg]Image 1 3000.00 4002.00 503.00 0.1146 0.0573 5.7296Image 2 3305.00 4005.00 499.00 0.1432 0.0859 -5.7296Image 3 3610.00 3995.00 505.00 0.1719 0.4584 2.8648Image 4 3613.00 4613.00 507.00 0.2865 -0.0573 185.6383Image 5 3303.00 4617.00 493.00 -0.1432 0.4011 173.0333Image 6 2997.00 4610.00 509.00 -0.1833 -0.2865 181.6276Table 5.3: EOPs of six bundle block images for simulation76
of bundle block adjustment is required prior to the actual experiment with real datato evaluate the performance of the proposed algorithms. A simulation can control themeasurement errors so random noises affect the overall geometry of a block a little.The individual observations are generated based on the general situation of bundleblock adjustment to estimate the properties of the proposed algorithms. A simulationallows the adjustment for geometric problems or conditions with various experiments.A spline is derived by three ground control points (3232, 4261, 18), (3335, 4343, 52),(3373, 4387, 34).Figure 5.3: Natural cubic splineIn this chapter, several factors which affect the estimates of exterior orientationparameters, spline parameters, and spline location parameters are implemented usingthe proposed bundle block adjustment model with the simulated image block and thereal image block.77
- Page 37 and 38: Tankovich[69] used linear features
- Page 39 and 40: (a) 0th order continuity (b) 1st or
- Page 41 and 42: Cardinal splineA Cardinal spline is
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- Page 45 and 46: For other polyline expressions, Aya
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- Page 49 and 50: ⎡⎢⎣2 11 4 11 4 1· · ·1 4 1
- Page 51 and 52: 3.2 Extended collinearity equation
- Page 53 and 54: R −1 = R T . The matrix R T (= R
- Page 55 and 56: dx p = M 1 dX C + M 2 dY C + M 3 dZ
- Page 57 and 58: In this research, the arc-length pa
- Page 59 and 60: =√∫ √√√ ()ti+1−f u′ (
- Page 61 and 62: This equation can be replaced with
- Page 63 and 64: order polynomial using Newton’s d
- Page 65 and 66: y collinearity equations, tangents
- Page 67 and 68: d tan(θ t ) = w′ (v ′ w − w
- Page 69 and 70: y each two points, which are four e
- Page 71 and 72: +M 14 db i3 + M 15 dc i0 + M 16 dc
- Page 73 and 74: collinearity model are described in
- Page 75 and 76: [ ] [ ] [ ]N11 N 12 ˆξ1 c1N12T =N
- Page 77 and 78: systematic errors in the image spac
- Page 79 and 80: interval based on the normal distri
- Page 81 and 82: 1 ∂Φ2 ∂l= (X C + d 1 l − a i
- Page 83 and 84: about splines, their relationships,
- Page 85 and 86: cubic spline in the image and the o
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- Page 91 and 92: ξ kiSP = [ da i0 da i1 da i2 da i3
- Page 93 and 94: Spline location parametersImage 1 I
- Page 95 and 96: Spline location parametersImage 1 I
- Page 97 and 98: 5.3 Recovery of EOPs and spline par
- Page 99 and 100: Table 5.7 expressed the convergence
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- Page 103 and 104: Vertical aerial photographData 9 Ju
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- Page 121 and 122: A 17 = t [2 − t 1 16 2 f(t 1) −
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- Page 125 and 126: BIBLIOGRAPHY[1] Ackerman, F., and V
- Page 127 and 128: [24] Haala, N., and G. Vosselman. 1
- Page 129 and 130: [49] Parian, J.A., and A. Gruen. 20
- Page 131: [73] Vosselman, G., and H. Veldhuis
Figure 5.2: Six image <strong>block</strong>Parameter X c [m] Y c [m] Z c [m] ω [deg] ϕ [deg] κ [deg]Image 1 3000.00 4002.00 503.00 0.1146 0.0573 5.7296Image 2 3305.00 4005.00 499.00 0.1432 0.0859 -5.7296Image 3 3610.00 3995.00 505.00 0.1719 0.4584 2.8648Image 4 3613.00 4613.00 507.00 0.2865 -0.0573 185.6383Image 5 3303.00 4617.00 493.00 -0.1432 0.4011 173.0333Image 6 2997.00 4610.00 509.00 -0.1833 -0.2865 181.6276Table 5.3: EOPs of six <strong>bundle</strong> <strong>block</strong> images for simulation76
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