Usability of Digital Cameras for Verifying Physically Based ...

More documents

Recommendations

Info

Figure 22: A Bayer filter mosaic is a color filter array for arranging RGB color filters on a square grid of photosensors [bay06]. and 1 Million for both red and blue filters. To recalculate a full 4 Megapixel RGB image a color interpolation called demosaicing has to be done. This algorithm estimates the missing RGB values by using information from the surrounding pixels. After this step, various image enhancement techniques like white balance, sharpening, contrast and brightness adjustments, noise reduction etc. are applied to the interpolated sensor data. The final image is usually either saved in JPEG or TIFF file format – JPEG format is more common because of the smaller file size due to compression. Figure 24 illustrates the individual steps of image processing done by camera software. Most prosumer-grade cameras provide two forms of output data: the RAW image data [SG06] and the final image (see figure 23). The RAW image data contains the actual values of each CCD sensor element. The final image contains the enhanced data and is usually converted to 8-bit and compressed with lossy compression algorithms. If we want to use the final image for verification purposes we have to have that in mind. Most camera manufacturers have created their very own raw file format – the 40
Figure 23: The RAW image data is converted to the final RGB value. Figure 24: The individual steps of color processing done by common digital cameras [raw06b]. 41
Page 1 and 2:
DISSERTATION Usability of Digital C
Page 3 and 4:
Kurzfassung Physically Based Render
Page 5 and 6: Acknowledgements I want to thank We
Page 7 and 8: 3 Colorimetry 32 3.1 Color Spaces .
Page 9 and 10: E.5 Treating the Camera as a Black
Page 11 and 12: 20 The CIE 1931 chromaticity diagra
Page 13 and 14: 53 (a) Density plot for using the c
Page 15 and 16: List of Tables 1 Camera settings th
Page 17 and 18: 1 Introduction In recent years, a l
Page 19 and 20: 1.3 Applications of Physically Base
Page 21 and 22: matter are calculated in XYZ space.
Page 23 and 24: Figure 2: A photograph of the real
Page 25 and 26: (a) Photo (b) Default (c) 2 Bounces
Page 27 and 28: y a light source on top of the cube
Page 29 and 30: 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: 4 Digital Cameras Pattanaik et al.
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 and 82: (a) (b) Figure 46: Standard deviati
Page 83 and 84: (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 125 and 126:
8 bit jpg 16 bit 91 17.21 17.11 17.
Page 127 and 128:
E.2 Using an ICC Profile 8 bit jpg
Page 129 and 130:
8 bit jpg 16 bit 62 16.10 16.08 16.
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 and 150:
[HLR00] Guowei Hong, M. Ronnier Luo
Page 151 and 152:
Color Imaging Conference, pages 250
Page 153:
[VMKK00] V. Volevich, K. Myszkowski
show all

Usability of Digital Cameras for Verifying Physically Based ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?