Usability of Digital Cameras for Verifying Physically Based ...

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[dea06] Dead/Hot Pixel Test: http://www.foto-freeware.de/ deadpixeltest.php, November 2006. [DM01] Frédéric Drago and Karol Myszkowski. Validation Proposal for Global Illumination and Rendering Techniques. Computers & Graphics, 25(3):511–518, 2001. [FS02] Paul D. Fleming and Abhay Sharma. Color Management and ICC Profiles; Cant Live Without It So Learn To Live With It! Gravure Magazine, August 2002. [GJB80] Franc Grum and C. James Bartleson. Optical Radiation Measure- ments, volume 2. Academic Press, Inc., 1980. [Gla95] Andrew S. Glassner. Principles of Digital Image Synthesis, volume 1. Morgan Kaufmann Publishers, Inc., 1995. [GM02] Phil Green and Lindsay MacDonald. Colour Engineering – Achiev- ing Device Independent Colour. John Wiley & Sons, Inc., 2002. [Gre99] Phil Green. Understanding Digital Color. Graphic Arts Technical Foundation, 1999. [GTGB84] Cindy M. Goral, Kenneth E. Torrance, Donald P. Greenberg, and Bennett Battaile. Modelling the Interaction of Light Between Dif- fuse Surfaces. In Computer Graphics (SIGGRAPH ’84 Proceed- ings), volume 18, pages 213–222, July 1984. [GTS + 97] Donald P. Greenberg, Kenneth E. Torrance, Shirley Shirley, James Arvo, James A. Ferwerda, Sumanta Pattanaik, Eric P. F. Lafortune, Walter Walter, Sing-Choong Foo, and Ben Trumbore. A Framework for Realistic Image Synthesis. In Turner Whitted, editor, SIGGRAPH 97 Conference Proceedings, Annual Conference Series, pages 477– 494. ACM SIGGRAPH, Addison Wesley, August 1997. ISBN 0- 89791-896-7. [HG83] R. A. Hall and D. P. Greenberg. A Testbed for Realistic Image Syn- thesis. IEEE Computer Graphics and Applications, 3:10–20, 1983. 132
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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
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 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: References [3dS06] 3D Studio Max: w
Page 151 and 152: Color Imaging Conference, pages 250
Page 153: [VMKK00] V. Volevich, K. Myszkowski
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