Usability of Digital Cameras for Verifying Physically Based ...

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1 2 3 4 124 5.03 7.19 6.68 2.10 125 9.41 10.55 11.20 12.32 126 2.53 3.36 0.41 3.06 127 5.02 5.55 4.32 5.35 128 2.67 2.69 2.98 2.32 129 6.25 5.96 5.30 5.51 130 3.66 4.33 2.59 4.09 131 1.94 1.95 2.52 1.05 132 5.69 5.28 4.98 4.79 133 3.03 3.74 1.83 3.49 134 1.82 1.81 2.43 0.65 135 6.52 5.96 5.82 5.50 136 3.41 4.08 2.32 3.85 137 1.92 1.99 2.51 1.26 138 6.26 5.76 5.60 5.31 139 2.99 3.07 3.08 3.07 140 6.53 6.94 6.18 6.77 Table 18: L ∗ a ∗ b ∗ differences for all 140 patches for linear polynomials when using the adaptive mapping. The patches are consecutively numbered from left to right, starting at the upper left corner of the color chart. For details on the used method see section 7.3. 120
E.4 Adaptive Mapping – Higher Order Polynomials 5 6 7 8 9 10 11 1 2.73 0.49 0.13 0.74 0.72 0.15 0.31 2 0.55 1.06 1.77 1.27 1.31 1.28 1.18 3 3.73 2.48 2.96 2.23 1.92 1.68 1.40 4 1.78 1.14 1.57 2.46 2.55 1.25 1.88 5 0.76 1.20 1.98 1.74 1.84 2.01 1.70 6 3.46 1.52 1.97 1.35 1.15 0.89 0.84 7 1.43 1.69 2.21 3.23 3.34 1.56 2.50 8 1.12 1.34 2.05 1.91 2.02 2.23 1.87 9 3.57 2.08 2.42 1.87 1.62 1.56 1.31 10 1.66 1.27 1.74 2.69 2.78 1.29 2.04 11 0.58 0.97 1.76 1.54 1.63 1.79 1.49 12 3.63 2.45 2.95 2.20 1.88 1.72 1.37 13 0.50 0.91 1.70 1.24 1.26 1.23 1.10 14 2.76 0.74 0.69 0.26 0.34 0.58 0.42 15 3.63 1.22 1.69 0.86 0.62 0.63 0.30 16 5.39 5.66 3.42 3.54 2.90 1.65 3.57 17 8.00 6.61 1.33 1.94 2.22 2.38 2.04 18 4.86 4.56 2.13 2.57 2.46 1.85 2.41 19 7.20 7.18 3.82 2.81 2.66 1.71 0.54 20 6.09 4.75 5.20 4.95 4.91 4.40 4.12 21 2.87 2.53 2.62 2.63 2.14 1.95 3.08 22 5.65 4.40 5.38 4.30 5.72 2.14 5.32 23 3.50 2.80 2.79 2.71 2.32 3.29 2.33 24 8.88 7.70 2.58 1.95 1.79 2.13 2.73 25 5.72 5.75 1.19 0.95 2.05 1.98 0.25 26 4.75 5.09 6.41 5.28 6.90 2.36 6.96 27 4.31 4.74 2.36 0.90 2.68 1.24 2.74 28 1.14 1.29 1.90 1.35 1.29 1.05 1.10 29 1.11 1.34 1.99 1.45 1.40 1.21 1.23 30 2.67 0.88 3.51 1.84 3.53 1.86 3.62 121
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DISSERTATION Usability of Digital C
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Kurzfassung Physically Based Render
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Acknowledgements I want to thank We
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3 Colorimetry 32 3.1 Color Spaces .
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E.5 Treating the Camera as a Black
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20 The CIE 1931 chromaticity diagra
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53 (a) Density plot for using the c
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List of Tables 1 Camera settings th
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1 Introduction In recent years, a l
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1.3 Applications of Physically Base
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matter are calculated in XYZ space.
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Figure 2: A photograph of the real
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(a) Photo (b) Default (c) 2 Bounces
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y a light source on top of the cube
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Figure 7: Points A to F were select
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Figure 9: A difference image of pho
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Figure 12: From top to bottom: a hi
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(a) Figure 13: (a) Left side: measu
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Figure 14: Six photocells were posi
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Figure 16: The left image shows a r
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(a) (b) Figure 18: (a) The validati
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shape of the caustic. 2.3 Analytica
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two test cases, but instead of the
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segments of the sphere and its actu
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of luminance [GJB80]. In XYZ color
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where L ∗ � � Y m = 903.3 Yn
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(a) (b) Figure 21: Chromaticity dia
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4 Digital Cameras Pattanaik et al.
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Figure 23: The RAW image data is co
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5 Physically Based Rendering System
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see section 7.4. By avoiding XYZ sp
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Figure 27: The sensor plane marking
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(a) (b) Figure 30: (a) ColorChecker
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available on MAC systems. We chose
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(a) (b) (c) Figure 34: Standard dev
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Figure 35: Eighty measurement spots
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(a) (b) (c) (d) Figure 37: (a) Lumi
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(a) (b) Figure 40: (a) Luminance di
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i \ j 0 1 2 3 4 5 6 7 8 9 10 11 12
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(a) (b) (c) (d) Figure 43: (a) Lumi
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(a) (b) Figure 46: Standard deviati
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(a) (b) Figure 49: (a) The measurem
Page 85 and 86: of each patch using a spectrophotom
Page 87 and 88: Figure 51: L ∗ a ∗ b ∗ differ
Page 89 and 90: (a) (b) Figure 53: (a) Density plot
Page 91 and 92: (a) (b) (c) Figure 55: Histograms o
Page 93 and 94: Using an ICC profile obviously impr
Page 95 and 96: (a) (b) (c) (d) Figure 58: Histogra
Page 97 and 98: 5 6 7 8 9 10 11 Min 0.50 0.49 0.13
Page 99 and 100: in the light transport simulation o
Page 101 and 102: the internal data of a camera and w
Page 103 and 104: etter results: One can measure the
Page 105 and 106: Figure 62: A Mathematica generated
Page 107 and 108: their internal color space. This mi
Page 109 and 110: Figure 66: Surface reflectance valu
Page 111 and 112: as bad compared to other methods. S
Page 113 and 114: in sufficient detail. The approach
Page 115 and 116: A Radiometric and Photometric Quant
Page 117 and 118: B.6 Goniophotometer A goniophotomet
Page 119 and 120: C.3 Color Chart Figure 68: A Konica
Page 121 and 122: D Web Resources of Validation Data
Page 123 and 124: 8 bit jpg 16 bit 29 11.58 11.52 11.
Page 127 and 128: E.2 Using an ICC Profile 8 bit jpg
Page 131 and 132: 8 bit jpg 16 bit 124 11.08 10.89 11
Page 133 and 134: 1 2 3 4 31 9.10 3.61 4.26 5.96 32 8
Page 135: 1 2 3 4 93 6.25 4.11 4.05 8.69 94 4
Page 139 and 140: 5 6 7 8 9 10 11 62 3.42 2.52 2.51 2
Page 141 and 142: 5 6 7 8 9 10 11 124 2.10 2.14 2.96
Page 143 and 144: R G B 31 -38.94 -25.49 29.26 32 -9.
Page 145 and 146: R G B 93 103.86 109.28 55.06 94 31.
Page 147 and 148: References [3dS06] 3D Studio Max: w
Page 149 and 150: [HLR00] Guowei Hong, M. Ronnier Luo
Page 151 and 152: Color Imaging Conference, pages 250
Page 153: [VMKK00] V. Volevich, K. Myszkowski
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