Usability of Digital Cameras for Verifying Physically Based ...

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[lcm06] Little CMS library: http://www.littlecms.com/, Novem- ber 2006. [Lig06] Lightscape: http://www.lightscape.com/, November 2006. [Lum06] Lumen Micro: http://www.lighting-technologies. com/, November 2006. [Mar99] John Mardaljevic. Daylight Simulation: Validation, Sky Models and Daylight Coefficients. Ph.d. dissertation, De Montfort University, Leicester, Institute of Energy and Sustainable Development, Dec 1999. [mat06] Mathematica: http://www.wolfram.com/, November 2006. [MCTG00] Ann McNamara, Alan Chalmers, Tom Troscianko, and Iain Gil- christ. Comparing Real and Synthetic Scenes using Human Judge- ments of Lightness. In B. Piroche and H. Rushmeier, editors, Pro- ceedings of the Eurographics Workshop. Eurographics, June 2000. [MF03] F. Maamari and M. Fontoynont. Analytical Tests for Investigating the Accuracy of Lighting Programs. Lighting Research and Technology, 35(3):225–242, 2003. [MK00] Karol Myszkowski and Tosiyasu L. Kunii. A Case Study Towards Validation of Global Illumination Algorithms: Progressive Hierarch- ical Radiosity with Clustering. The Visual Computer, 16(5):271–288, 2000. [MRC + 86] Gary W. Meyer, Holly E. Rushmeier, Michael F. Cohen, Donald P. Greenberg, and Kenneth E. Torrance. An Experimental Evaluation of Computer Graphics Imagery. ACM Trans. Graph., 5(1):30–50, 1986. [PFTG97] Sumanta N. Pattanaik, James A. Ferwerda, Kenneth E. Torrance, and Donald P. Greenberg. Validation of Global Illumination Solutions Through CCD Camera Measurements. In Proceedings of the Fifth 134
Color Imaging Conference, pages 250–253. Society for Imaging Sci- ence and Technology, November 1997. [Pho75] Bui Tuong Phong. Illumination for Computer Generated Pictures. Graphics and Image Processing, 18(6):311–317, 1975. [PSM93] R. Perez, R. Seals, and J. Michalsky. All-Weather Model for Sky Luminance Distribution - Preliminary Configuration and Validation. Solar Energy, 50(3):235–245, 1993. [raw06a] Dcraw: http://www.cybercom.net/ ∼ dcoffin/dcraw/, November 2006. [raw06b] Raw File Format Tutorial: http://www. cambridgeincolour.com/tutorials/ RAW-file-format.htm, November 2006. [Rea06] RealReflect Project http://www.realreflect.org/, November 2006. [Ren06] RenderPark: A Test-Bed System for Global Illumination http:// www.renderpark.be/, November 2006. [SAWG91] Francois X. Sillion, James A. Arvo, Westin Westin, and Donald P. Greenberg. A Global Illumination Solution for General Reflectance Distributions. In Thomas W. Sederberg, editor, Proceedings of the ACM SIGGRAPH Conference on Computer Graphics (SIGGRAPH ’91), pages 187–196, Las Vegas, Nevada, USA, July 1991. ACM Press. [SG06] Uwe Steinmüller and Jürgen Gulbins. Die Kunst der RAW- Konvertierung – RAW-Files bearbeiten mit führenden RAW- Konvertern. dpunkt.verlag, 2006. [Sha04] Abhay Sharma. Understanding Color Management. Thomson Del- mar Learning, 2004. [SKKA01] L. Szirmay-Kalos, L. Kovás, and Ali Mohamed Abbas. Testing Monte-Carlo Global Illumination Methods with Analytically Com- putable Scenes. In Winter School of Computer Graphics Conf., 2001. 135
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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
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of each patch using a spectrophotom
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Figure 51: L ∗ a ∗ b ∗ differ
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(a) (b) Figure 53: (a) Density plot
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(a) (b) (c) Figure 55: Histograms o
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Using an ICC profile obviously impr
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(a) (b) (c) (d) Figure 58: Histogra
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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 and 136: 1 2 3 4 93 6.25 4.11 4.05 8.69 94 4
Page 137 and 138: E.4 Adaptive Mapping - Higher Order
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: [HLR00] Guowei Hong, M. Ronnier Luo
Page 153: [VMKK00] V. Volevich, K. Myszkowski
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