COMPOSITION
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Composition and The Expressive Nature Of Light
Read more: Composition and The Expressive Nature Of Lighthttp://www.huffingtonpost.com/bill-danskin/post_12457_b_10777222.html
George Sand once said “ The artist vocation is to send light into the human heart.”
DESIGN
COLOR
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Björn Ottosson – OKlch color space
Read more: Björn Ottosson – OKlch color spaceBjörn Ottosson proposed OKlch in 2020 to create a color space that can closely mimic how color is perceived by the human eye, predicting perceived lightness, chroma, and hue.
The OK in OKLCH stands for Optimal Color.
- L: Lightness (the perceived brightness of the color)
- C: Chroma (the intensity or saturation of the color)
- H: Hue (the actual color, such as red, blue, green, etc.)
Also read:
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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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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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Willem Zwarthoed – Aces gamut in VFX production pdf
Read more: Willem Zwarthoed – Aces gamut in VFX production pdfhttps://www.provideocoalition.com/color-management-part-12-introducing-aces/
Local copy:
https://www.slideshare.net/hpduiker/acescg-a-common-color-encoding-for-visual-effects-applications
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Björn Ottosson – How software gets color wrong
Read more: Björn Ottosson – How software gets color wronghttps://bottosson.github.io/posts/colorwrong/
Most software around us today are decent at accurately displaying colors. Processing of colors is another story unfortunately, and is often done badly.
To understand what the problem is, let’s start with an example of three ways of blending green and magenta:
- Perceptual blend – A smooth transition using a model designed to mimic human perception of color. The blending is done so that the perceived brightness and color varies smoothly and evenly.
- Linear blend – A model for blending color based on how light behaves physically. This type of blending can occur in many ways naturally, for example when colors are blended together by focus blur in a camera or when viewing a pattern of two colors at a distance.
- sRGB blend – This is how colors would normally be blended in computer software, using sRGB to represent the colors.
Let’s look at some more examples of blending of colors, to see how these problems surface more practically. The examples use strong colors since then the differences are more pronounced. This is using the same three ways of blending colors as the first example.
Instead of making it as easy as possible to work with color, most software make it unnecessarily hard, by doing image processing with representations not designed for it. Approximating the physical behavior of light with linear RGB models is one easy thing to do, but more work is needed to create image representations tailored for image processing and human perception.
Also see:
LIGHTING
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Disney’s Moana Island Scene – Free data set
Read more: Disney’s Moana Island Scene – Free data sethttps://www.disneyanimation.com/resources/moana-island-scene/
This data set contains everything necessary to render a version of the Motunui island featured in the 2016 film Moana.
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Bella – Fast Spectral Rendering
Read more: Bella – Fast Spectral Rendering
Bella works in spectral space, allowing effects such as BSDF wavelength dependency, diffraction, or atmosphere to be modeled far more accurately than in color space.
https://superrendersfarm.com/blog/uncategorized/bella-a-new-spectral-physically-based-renderer/
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NVidia DiffusionRenderer – Neural Inverse and Forward Rendering with Video Diffusion Models. How NVIDIA reimagined relighting
Read more: NVidia DiffusionRenderer – Neural Inverse and Forward Rendering with Video Diffusion Models. How NVIDIA reimagined relightinghttps://www.fxguide.com/quicktakes/diffusing-reality-how-nvidia-reimagined-relighting/
https://research.nvidia.com/labs/toronto-ai/DiffusionRenderer/
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Gamma correction
Read more: Gamma correction
http://www.normankoren.com/makingfineprints1A.html#Gammabox
https://en.wikipedia.org/wiki/Gamma_correction
http://www.photoscientia.co.uk/Gamma.htm
https://www.w3.org/Graphics/Color/sRGB.html
http://www.eizoglobal.com/library/basics/lcd_display_gamma/index.html
https://forum.reallusion.com/PrintTopic308094.aspx
Basically, gamma is the relationship between the brightness of a pixel as it appears on the screen, and the numerical value of that pixel. Generally Gamma is just about defining relationships.
Three main types:
– Image Gamma encoded in images
– Display Gammas encoded in hardware and/or viewing time
– System or Viewing Gamma which is the net effect of all gammas when you look back at a final image. In theory this should flatten back to 1.0 gamma.
(more…)
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