Usability of Digital Cameras for Verifying Physically Based ...

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(a) (b) Figure 48: (a) The measurement points at 45 ◦ ; (b) absolute difference in luminance for the 20 measurement points, accordingly. the luminance difference distribution might be more even: • we rotated it by 45 ◦ , • we placed it at a height of 24.5cm and • we put it inside a black box. Figures 48, 49 and 50 show (a) a photo of the measurement setup and (b) the relative error in luminance, respectively. During the measurement process the light cabinet again was covered with cardboard. The standard deviations are 26.97, 27.93 and 7.39, respectively. All three tests did not bring the desired im- provement, as even the setup including the black box has a higher standard deviation than the plain light cabinet at 100% (standard deviation: 6.28). In order to decide which dimmer setting to use, we took one photograph each at dimmer settings 100%, 50%, 25% and 15%. The camera settings used are shown in table 7. As the exposure time was twice as long when the light intensity was halved, the images theoretically should be equal, or at least very similar. We used two methods to judge the quality of the images: • We opened the images in GretagMacbeth ProfileMaker “Camera” Tab, be- cause in one of our methods (see section 7.2) we use this software. Profile- Maker checks, if the image can be used for generating an ICC profile (e.g. it analyzes the luminance difference distribution on the ColorChecker). We 66
(a) (b) Figure 49: (a) The measurement points placed at a height of 24.5cm; (b) absolute difference in luminance for the 20 measurement points, accordingly. (a) (b) Figure 50: (a) The measurement points put inside a black box; (b) absolute difference in luminance for the 20 measurement points, accordingly. 67
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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
Page 31 and 32: Figure 9: A difference image of pho
Page 33 and 34: Figure 12: From top to bottom: a hi
Page 35 and 36: (a) Figure 13: (a) Left side: measu
Page 37 and 38: Figure 14: Six photocells were posi
Page 39 and 40: Figure 16: The left image shows a r
Page 41 and 42: (a) (b) Figure 18: (a) The validati
Page 43 and 44: shape of the caustic. 2.3 Analytica
Page 45 and 46: two test cases, but instead of the
Page 47 and 48: segments of the sphere and its actu
Page 49 and 50: of luminance [GJB80]. In XYZ color
Page 51 and 52: where L ∗ � � Y m = 903.3 Yn
Page 53 and 54: (a) (b) Figure 21: Chromaticity dia
Page 55 and 56: 4 Digital Cameras Pattanaik et al.
Page 57 and 58: Figure 23: The RAW image data is co
Page 59 and 60: 5 Physically Based Rendering System
Page 61 and 62: see section 7.4. By avoiding XYZ sp
Page 63 and 64: Figure 27: The sensor plane marking
Page 65 and 66: (a) (b) Figure 30: (a) ColorChecker
Page 67 and 68: available on MAC systems. We chose
Page 69 and 70: (a) (b) (c) Figure 34: Standard dev
Page 71 and 72: Figure 35: Eighty measurement spots
Page 73 and 74: (a) (b) (c) (d) Figure 37: (a) Lumi
Page 75 and 76: (a) (b) Figure 40: (a) Luminance di
Page 77 and 78: i \ j 0 1 2 3 4 5 6 7 8 9 10 11 12
Page 79 and 80: (a) (b) (c) (d) Figure 43: (a) Lumi
Page 81: (a) (b) Figure 46: Standard deviati
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
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1 2 3 4 31 9.10 3.61 4.26 5.96 32 8
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1 2 3 4 93 6.25 4.11 4.05 8.69 94 4
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E.4 Adaptive Mapping - Higher Order
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5 6 7 8 9 10 11 62 3.42 2.52 2.51 2
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5 6 7 8 9 10 11 124 2.10 2.14 2.96
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R G B 31 -38.94 -25.49 29.26 32 -9.
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R G B 93 103.86 109.28 55.06 94 31.
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References [3dS06] 3D Studio Max: w
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[HLR00] Guowei Hong, M. Ronnier Luo
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Color Imaging Conference, pages 250
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[VMKK00] V. Volevich, K. Myszkowski
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