COMPOSITION
DESIGN
COLOR
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Tim Kang – calibrated white light values in sRGB color space
Read more: Tim Kang – calibrated white light values in sRGB color space8bit sRGB encoded
2000K 255 139 22
2700K 255 172 89
3000K 255 184 109
3200K 255 190 122
4000K 255 211 165
4300K 255 219 178
D50 255 235 205
D55 255 243 224
D5600 255 244 227
D6000 255 249 240
D65 255 255 255
D10000 202 221 255
D20000 166 196 2558bit Rec709 Gamma 2.4
2000K 255 145 34
2700K 255 177 97
3000K 255 187 117
3200K 255 193 129
4000K 255 214 170
4300K 255 221 182
D50 255 236 208
D55 255 243 226
D5600 255 245 229
D6000 255 250 241
D65 255 255 255
D10000 204 222 255
D20000 170 199 2558bit Display P3 encoded
2000K 255 154 63
2700K 255 185 109
3000K 255 195 127
3200K 255 201 138
4000K 255 219 176
4300K 255 225 187
D50 255 239 212
D55 255 245 228
D5600 255 246 231
D6000 255 251 242
D65 255 255 255
D10000 208 223 255
D20000 175 199 25510bit Rec2020 PQ (100 nits)
2000K 520 435 273
2700K 520 466 358
3000K 520 475 384
3200K 520 480 399
4000K 520 495 446
4300K 520 500 458
D50 520 510 482
D55 520 514 497
D5600 520 514 500
D6000 520 517 509
D65 520 520 520
D10000 479 489 520
D20000 448 464 520
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Capturing textures albedo
Read more: Capturing textures albedoBuilding a Portable PBR Texture Scanner by Stephane Lb
http://rtgfx.com/pbr-texture-scanner/
How To Split Specular And Diffuse In Real Images, by John Hable
http://filmicworlds.com/blog/how-to-split-specular-and-diffuse-in-real-images/Capturing albedo using a Spectralon
https://www.activision.com/cdn/research/Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdfReal_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf
Spectralon is a teflon-based pressed powderthat comes closest to being a pure Lambertian diffuse material that reflects 100% of all light. If we take an HDR photograph of the Spectralon alongside the material to be measured, we can derive thediffuse albedo of that material.
The process to capture diffuse reflectance is very similar to the one outlined by Hable.
1. We put a linear polarizing filter in front of the camera lens and a second linear polarizing filterin front of a modeling light or a flash such that the two filters are oriented perpendicular to eachother, i.e. cross polarized.
2. We place Spectralon close to and parallel with the material we are capturing and take brack-eted shots of the setup7. Typically, we’ll take nine photographs, from -4EV to +4EV in 1EVincrements.
3. We convert the bracketed shots to a linear HDR image. We found that many HDR packagesdo not produce an HDR image in which the pixel values are linear. PTGui is an example of apackage which does generate a linear HDR image. At this point, because of the cross polarization,the image is one of surface diffuse response.
4. We open the file in Photoshop and normalize the image by color picking the Spectralon, filling anew layer with that color and setting that layer to “Divide”. This sets the Spectralon to 1 in theimage. All other color values are relative to this so we can consider them as diffuse albedo.
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HDR and Color
Read more: HDR and Colorhttps://www.soundandvision.com/content/nits-and-bits-hdr-and-color
In HD we often refer to the range of available colors as a color gamut. Such a color gamut is typically plotted on a two-dimensional diagram, called a CIE chart, as shown in at the top of this blog. Each color is characterized by its x/y coordinates.
Good enough for government work, perhaps. But for HDR, with its higher luminance levels and wider color, the gamut becomes three-dimensional.
For HDR the color gamut therefore becomes a characteristic we now call the color volume. It isn’t easy to show color volume on a two-dimensional medium like the printed page or a computer screen, but one method is shown below. As the luminance becomes higher, the picture eventually turns to white. As it becomes darker, it fades to black. The traditional color gamut shown on the CIE chart is simply a slice through this color volume at a selected luminance level, such as 50%.
Three different color volumes—we still refer to them as color gamuts though their third dimension is important—are currently the most significant. The first is BT.709 (sometimes referred to as Rec.709), the color gamut used for pre-UHD/HDR formats, including standard HD.
The largest is known as BT.2020; it encompasses (roughly) the range of colors visible to the human eye (though ET might find it insufficient!).
Between these two is the color gamut used in digital cinema, known as DCI-P3.
sRGB
D65
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StudioBinder.com – CRI color rendering index
Read more: StudioBinder.com – CRI color rendering indexwww.studiobinder.com/blog/what-is-color-rendering-index
“The Color Rendering Index is a measurement of how faithfully a light source reveals the colors of whatever it illuminates, it describes the ability of a light source to reveal the color of an object, as compared to the color a natural light source would provide. The highest possible CRI is 100. A CRI of 100 generally refers to a perfect black body, like a tungsten light source or the sun. ”
www.pixelsham.com/2021/04/28/types-of-film-lights-and-their-efficiency
LIGHTING
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StudioBinder.com – CRI color rendering index
Read more: StudioBinder.com – CRI color rendering indexwww.studiobinder.com/blog/what-is-color-rendering-index
“The Color Rendering Index is a measurement of how faithfully a light source reveals the colors of whatever it illuminates, it describes the ability of a light source to reveal the color of an object, as compared to the color a natural light source would provide. The highest possible CRI is 100. A CRI of 100 generally refers to a perfect black body, like a tungsten light source or the sun. ”
www.pixelsham.com/2021/04/28/types-of-film-lights-and-their-efficiency
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Cinematographers Blueprint 300dpi poster
Read more: Cinematographers Blueprint 300dpi posterThe 300dpi digital poster is now available to all PixelSham.com subscribers.
If you have already subscribed and wish a copy, please send me a note through the contact page.
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Fast, optimized ‘for’ pixel loops with OpenCV and Python to create tone mapped HDR images
Read more: Fast, optimized ‘for’ pixel loops with OpenCV and Python to create tone mapped HDR imageshttps://pyimagesearch.com/2017/08/28/fast-optimized-for-pixel-loops-with-opencv-and-python/
https://learnopencv.com/exposure-fusion-using-opencv-cpp-python/
Exposure Fusion is a method for combining images taken with different exposure settings into one image that looks like a tone mapped High Dynamic Range (HDR) image.
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