COMPOSITION
DESIGN
COLOR
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THOMAS MANSENCAL – The Apparent Simplicity of RGB Rendering
Read more: THOMAS MANSENCAL – The Apparent Simplicity of RGB Rendering
https://thomasmansencal.substack.com/p/the-apparent-simplicity-of-rgb-rendering
The primary goal of physically-based rendering (PBR) is to create a simulation that accurately reproduces the imaging process of electro-magnetic spectrum radiation incident to an observer. This simulation should be indistinguishable from reality for a similar observer.
Because a camera is not sensitive to incident light the same way than a human observer, the images it captures are transformed to be colorimetric. A project might require infrared imaging simulation, a portion of the electro-magnetic spectrum that is invisible to us. Radically different observers might image the same scene but the act of observing does not change the intrinsic properties of the objects being imaged. Consequently, the physical modelling of the virtual scene should be independent of the observer.
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FXGuide – ACES 2.0 with ILM’s Alex Fry
Read more: FXGuide – ACES 2.0 with ILM’s Alex Fry
https://draftdocs.acescentral.com/background/whats-new/
ACES 2.0 is the second major release of the components that make up the ACES system. The most significant change is a new suite of rendering transforms whose design was informed by collected feedback and requests from users of ACES 1. The changes aim to improve the appearance of perceived artifacts and to complete previously unfinished components of the system, resulting in a more complete, robust, and consistent product.
Highlights of the key changes in ACES 2.0 are as follows:
- New output transforms, including:
- A less aggressive tone scale
- More intuitive controls to create custom outputs to non-standard displays
- Robust gamut mapping to improve perceptual uniformity
- Improved performance of the inverse transforms
- Enhanced AMF specification
- An updated specification for ACES Transform IDs
- OpenEXR compression recommendations
- Enhanced tools for generating Input Transforms and recommended procedures for characterizing prosumer cameras
- Look Transform Library
- Expanded documentation
Rendering Transform
The most substantial change in ACES 2.0 is a complete redesign of the rendering transform.
ACES 2.0 was built as a unified system, rather than through piecemeal additions. Different deliverable outputs “match” better and making outputs to display setups other than the provided presets is intended to be user-driven. The rendering transforms are less likely to produce undesirable artifacts “out of the box”, which means less time can be spent fixing problematic images and more time making pictures look the way you want.
Key design goals
- Improve consistency of tone scale and provide an easy to use parameter to allow for outputs between preset dynamic ranges
- Minimize hue skews across exposure range in a region of same hue
- Unify for structural consistency across transform type
- Easy to use parameters to create outputs other than the presets
- Robust gamut mapping to improve harsh clipping artifacts
- Fill extents of output code value cube (where appropriate and expected)
- Invertible – not necessarily reversible, but Output > ACES > Output round-trip should be possible
- Accomplish all of the above while maintaining an acceptable “out-of-the box” rendering
- New output transforms, including:
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GretagMacbeth Color Checker Numeric Values and Middle Gray
Read more: GretagMacbeth Color Checker Numeric Values and Middle GrayThe human eye perceives half scene brightness not as the linear 50% of the present energy (linear nature values) but as 18% of the overall brightness. We are biased to perceive more information in the dark and contrast areas. A Macbeth chart helps with calibrating back into a photographic capture into this “human perspective” of the world.
https://en.wikipedia.org/wiki/Middle_gray
In photography, painting, and other visual arts, middle gray or middle grey is a tone that is perceptually about halfway between black and white on a lightness scale in photography and printing, it is typically defined as 18% reflectance in visible light
Light meters, cameras, and pictures are often calibrated using an 18% gray card[4][5][6] or a color reference card such as a ColorChecker. On the assumption that 18% is similar to the average reflectance of a scene, a grey card can be used to estimate the required exposure of the film.
https://en.wikipedia.org/wiki/ColorChecker
The exposure meter in the camera does not know whether the subject itself is bright or not. It simply measures the amount of light that comes in, and makes a guess based on that. The camera will aim for 18% gray independently, meaning if you take a photo of an entirely white surface, and an entirely black surface you should get two identical images which both are gray (at least in theory). Thus enters the Macbeth chart.
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Note that Chroma Key Green is reasonably close to an 18% gray reflectance.
http://www.rags-int-inc.com/PhotoTechStuff/MacbethTarget/
No Camera Data 
https://upload.wikimedia.org/wikipedia/commons/b/b4/CIE1931xy_ColorChecker_SMIL.svg
RGB coordinates of the Macbeth ColorChecker
https://pdfs.semanticscholar.org/0e03/251ad1e6d3c3fb9cb0b1f9754351a959e065.pdf
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OpenColorIO standard
Read more: OpenColorIO standardhttps://www.provideocoalition.com/color-management-part-11-introducing-opencolorio/
OpenColorIO (OCIO) is a new open source project from Sony Imageworks.
Based on development started in 2003, OCIO enables color transforms and image display to be handled in a consistent manner across multiple graphics applications. Unlike other color management solutions, OCIO is geared towards motion-picture post production, with an emphasis on visual effects and animation color pipelines.
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Sensitivity of human eye
Read more: Sensitivity of human eyehttp://www.wikilectures.eu/index.php/Spectral_sensitivity_of_the_human_eye
http://www.normankoren.com/Human_spectral_sensitivity_small.jpg
Spectral sensitivity of eye is influenced by light intensity. And the light intensity determines the level of activity of cones cell and rod cell. This is the main characteristic of human vision. Sensitivity to individual colors, in other words, wavelengths of the light spectrum, is explained by the RGB (red-green-blue) theory. This theory assumed that there are three kinds of cones. It’s selectively sensitive to red (700-630 nm), green (560-500 nm), and blue (490-450 nm) light. And their mutual interaction allow to perceive all colors of the spectrum.
http://weeklysciencequiz.blogspot.com/2013/01/violet-skies-are-for-birds.html
Sensitivity of human eye Sensitivity of human eyes to light increase with the decrease in light intensity. In day-light condition, the cones cell is responding to this condition. And the eye is most sensitive at 555 nm. In darkness condition, the rod cell is responding to this condition. And the eye is most sensitive at 507 nm.
As light intensity decreases, cone function changes more effective way. And when decrease the light intensity, it prompt to accumulation of rhodopsin. Furthermore, in activates rods, it allow to respond to stimuli of light in much lower intensity.
The three curves in the figure above shows the normalized response of an average human eye to various amounts of ambient light. The shift in sensitivity occurs because two types of photoreceptors called cones and rods are responsible for the eye’s response to light. The curve on the right shows the eye’s response under normal lighting conditions and this is called the photopic response. The cones respond to light under these conditions.
As mentioned previously, cones are composed of three different photo pigments that enable color perception. This curve peaks at 555 nanometers, which means that under normal lighting conditions, the eye is most sensitive to a yellowish-green color. When the light levels drop to near total darkness, the response of the eye changes significantly as shown by the scotopic response curve on the left. At this level of light, the rods are most active and the human eye is more sensitive to the light present, and less sensitive to the range of color. Rods are highly sensitive to light but are comprised of a single photo pigment, which accounts for the loss in ability to discriminate color. At this very low light level, sensitivity to blue, violet, and ultraviolet is increased, but sensitivity to yellow and red is reduced. The heavier curve in the middle represents the eye’s response at the ambient light level found in a typical inspection booth. This curve peaks at 550 nanometers, which means the eye is most sensitive to yellowish-green color at this light level. Fluorescent penetrant inspection materials are designed to fluoresce at around 550 nanometers to produce optimal sensitivity under dim lighting conditions.
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Colormaxxing – What if I told you that rgb(255, 0, 0) is not actually the reddest red you can have in your browser?
Read more: Colormaxxing – What if I told you that rgb(255, 0, 0) is not actually the reddest red you can have in your browser?https://karuna.dev/colormaxxing
https://webkit.org/blog-files/color-gamut/comparison.html
https://oklch.com/#70,0.1,197,100
LIGHTING
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Practical Aspects of Spectral Data and LEDs in Digital Content Production and Virtual Production – SIGGRAPH 2022
Read more: Practical Aspects of Spectral Data and LEDs in Digital Content Production and Virtual Production – SIGGRAPH 2022
Comparison to the commercial side
https://www.ecolorled.com/blog/detail/what-is-rgb-rgbw-rgbic-strip-lights
RGBW (RGB + White) LED strip uses a 4-in-1 LED chip made up of red, green, blue, and white.
RGBWW (RGB + White + Warm White) LED strip uses either a 5-in-1 LED chip with red, green, blue, white, and warm white for color mixing. The only difference between RGBW and RGBWW is the intensity of the white color. The term RGBCCT consists of RGB and CCT. CCT (Correlated Color Temperature) means that the color temperature of the led strip light can be adjusted to change between warm white and white. Thus, RGBWW strip light is another name of RGBCCT strip.
RGBCW is the acronym for Red, Green, Blue, Cold, and Warm. These 5-in-1 chips are used in supper bright smart LED lighting products
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DiffusionLight: HDRI Light Probes for Free by Painting a Chrome Ball
Read more: DiffusionLight: HDRI Light Probes for Free by Painting a Chrome Ballhttps://diffusionlight.github.io/
https://github.com/DiffusionLight/DiffusionLight
https://github.com/DiffusionLight/DiffusionLight?tab=MIT-1-ov-file#readme
https://colab.research.google.com/drive/15pC4qb9mEtRYsW3utXkk-jnaeVxUy-0S
“a simple yet effective technique to estimate lighting in a single input image. Current techniques rely heavily on HDR panorama datasets to train neural networks to regress an input with limited field-of-view to a full environment map. However, these approaches often struggle with real-world, uncontrolled settings due to the limited diversity and size of their datasets. To address this problem, we leverage diffusion models trained on billions of standard images to render a chrome ball into the input image. Despite its simplicity, this task remains challenging: the diffusion models often insert incorrect or inconsistent objects and cannot readily generate images in HDR format. Our research uncovers a surprising relationship between the appearance of chrome balls and the initial diffusion noise map, which we utilize to consistently generate high-quality chrome balls. We further fine-tune an LDR difusion model (Stable Diffusion XL) with LoRA, enabling it to perform exposure bracketing for HDR light estimation. Our method produces convincing light estimates across diverse settings and demonstrates superior generalization to in-the-wild scenarios.”
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Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering and Denoising for HDR View Synthesis
Read more: Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering and Denoising for HDR View Synthesishttps://srameo.github.io/projects/le3d/
LE3D is a method for real-time HDR view synthesis from RAW images. It is particularly effective for nighttime scenes.
https://github.com/Srameo/LE3D
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The Color of Infinite Temperature
Read more: The Color of Infinite TemperatureThis is the color of something infinitely hot.
Of course you’d instantly be fried by gamma rays of arbitrarily high frequency, but this would be its spectrum in the visible range.
johncarlosbaez.wordpress.com/2022/01/16/the-color-of-infinite-temperature/
This is also the color of a typical neutron star. They’re so hot they look the same.
It’s also the color of the early Universe!This was worked out by David Madore.
The color he got is sRGB(148,177,255).
www.htmlcsscolor.com/hex/94B1FFAnd according to the experts who sip latte all day and make up names for colors, this color is called ‘Perano’.
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LUX vs LUMEN vs NITS vs CANDELA – What is the difference
Read more: LUX vs LUMEN vs NITS vs CANDELA – What is the differenceMore details here: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs Illuminance
https://www.inhouseav.com.au/blog/beginners-guide-nits-lumens-brightness/
Candela
Candela is the basic unit of measure of the entire volume of light intensity from any point in a single direction from a light source. Note the detail: it measures the total volume of light within a certain beam angle and direction.
While the luminance of starlight is around 0.001 cd/m2, that of a sunlit scene is around 100,000 cd/m2, which is a hundred millions times higher. The luminance of the sun itself is approximately 1,000,000,000 cd/m2.NIT
https://en.wikipedia.org/wiki/Candela_per_square_metre
The candela per square metre (symbol: cd/m2) is the unit of luminance in the International System of Units (SI). The unit is based on the candela, the SI unit of luminous intensity, and the square metre, the SI unit of area. The nit (symbol: nt) is a non-SI name also used for this unit (1 nt = 1 cd/m2).[1] The term nit is believed to come from the Latin word nitēre, “to shine”. As a measure of light emitted per unit area, this unit is frequently used to specify the brightness of a display device.
NIT and cd/m2 (candela power) represent the same thing and can be used interchangeably. One nit is equivalent to one candela per square meter, where the candela is the amount of light which has been emitted by a common tallow candle, but NIT is not part of the International System of Units (abbreviated SI, from Systeme International, in French).
It’s easiest to think of a TV as emitting light directly, in much the same way as the Sun does. Nits are simply the measurement of the level of light (luminance) in a given area which the emitting source sends to your eyes or a camera sensor.
The Nit can be considered a unit of visible-light intensity which is often used to specify the brightness level of an LCD.
1 Nit is approximately equal to 3.426 Lumens. To work out a comparable number of Nits to Lumens, you need to multiply the number of Nits by 3.426. If you know the number of Lumens, and wish to know the Nits, simply divide the number of Lumens by 3.426.
Most consumer desktop LCDs have Nits of 200 to 300, the average TV most likely has an output capability of between 100 and 200 Nits, and an HDR TV ranges from 400 to 1,500 Nits.
Virtual Production sets currently sport around 6000 NIT ceiling and 1000 NIT wall panels.The ambient brightness of a sunny day with clear blue skies is between 7000-10,000 nits (between 3000-7000 nits for overcast skies and indirect sunlight).
A bright sunny day can have specular highlights that reach over 100,000 nits. Direct sunlight is around 1,600,000,000 nits.
10,000 nits is also the typical brightness of a fluorescent tube – bright, but not painful to look at.
https://www.displaydaily.com/article/display-daily/dolby-vision-vs-hdr10-clarified
Tests showed that a “black level” of 0.005 nits (cd/m²) satisfied the vast majority of viewers. While 0.005 nits is very close to true black, Griffis says Dolby can go down to a black of 0.0001 nits, even though there is no need or ability for displays to get that dark today.
How bright is white? Dolby says the range of 0.005 nits – 10,000 nits satisfied 84% of the viewers in their viewing tests.
The brightest consumer HDR displays today are about 1,500 nits. Professional displays where HDR content is color-graded can achieve up to 4,000 nits peak brightness.High brightness that would be in danger of damaging the eye would be in the neighborhood of 250,000 nits.
Lumens
Lumen is a measure of how much light is emitted (luminance, luminous flux) by an object. It indicates the total potential amount of light from a light source that is visible to the human eye.
Lumen is commonly used in the context of light bulbs or video-projectors as a metric for their brightness power.Lumen is used to describe light output, and about video projectors, it is commonly referred to as ANSI Lumens. Simply put, lumens is how to find out how bright a LED display is. The higher the lumens, the brighter to display!
Technically speaking, a Lumen is the SI unit of luminous flux, which is equal to the amount of light which is emitted per second in a unit solid angle of one steradian from a uniform source of one-candela intensity radiating in all directions.
LUX
Lux (lx) or often Illuminance, is a photometric unit along a given area, which takes in account the sensitivity of human eye to different wavelenghts. It is the measure of light at a specific distance within a specific area at that distance. Often used to measure the incidental sun’s intensity.
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