COMPOSITION
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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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Composition – cinematography Cheat Sheet
Read more: Composition – cinematography Cheat Sheet
Where is our eye attracted first? Why?
Size. Focus. Lighting. Color.
Size. Mr. White (Harvey Keitel) on the right.
Focus. He’s one of the two objects in focus.
Lighting. Mr. White is large and in focus and Mr. Pink (Steve Buscemi) is highlighted by
a shaft of light.
Color. Both are black and white but the read on Mr. White’s shirt now really stands out.
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What type of lighting?
DESIGN
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Myriam Catrin – amazing design
Read more: Myriam Catrin – amazing designhttps://www.artstation.com/myriamcatrin
Creator of the comic book ” Passages. Book I” released with @therealarttitude
https://arttitudebootleg.bigcartel.com/product/passages-myriam-catrin
instagram/ FB page: @myriamcatrin / @MyriamCatrinComics
COLOR
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Capturing the world in HDR for real time projects – Call of Duty: Advanced Warfare
Read more: Capturing the world in HDR for real time projects – Call of Duty: Advanced WarfareReal-World Measurements for Call of Duty: Advanced Warfare
www.activision.com/cdn/research/Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf
Local version
Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf
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Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color picking
Read more: Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color pickinghttps://bottosson.github.io/misc/colorpicker
https://bottosson.github.io/posts/colorpicker/
https://www.smashingmagazine.com/2024/10/interview-bjorn-ottosson-creator-oklab-color-space/
One problem with sRGB is that in a gradient between blue and white, it becomes a bit purple in the middle of the transition. That’s because sRGB really isn’t created to mimic how the eye sees colors; rather, it is based on how CRT monitors work. That means it works with certain frequencies of red, green, and blue, and also the non-linear coding called gamma. It’s a miracle it works as well as it does, but it’s not connected to color perception. When using those tools, you sometimes get surprising results, like purple in the gradient.
There were also attempts to create simple models matching human perception based on XYZ, but as it turned out, it’s not possible to model all color vision that way. Perception of color is incredibly complex and depends, among other things, on whether it is dark or light in the room and the background color it is against. When you look at a photograph, it also depends on what you think the color of the light source is. The dress is a typical example of color vision being very context-dependent. It is almost impossible to model this perfectly.
I based Oklab on two other color spaces, CIECAM16 and IPT. I used the lightness and saturation prediction from CIECAM16, which is a color appearance model, as a target. I actually wanted to use the datasets used to create CIECAM16, but I couldn’t find them.
IPT was designed to have better hue uniformity. In experiments, they asked people to match light and dark colors, saturated and unsaturated colors, which resulted in a dataset for which colors, subjectively, have the same hue. IPT has a few other issues but is the basis for hue in Oklab.
In the Munsell color system, colors are described with three parameters, designed to match the perceived appearance of colors: Hue, Chroma and Value. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. Modern color spaces and models, such as CIELAB, Cam16 and Björn Ottosson own Oklab, are very similar in their construction.

By far the most used color spaces today for color picking are HSL and HSV, two representations introduced in the classic 1978 paper “Color Spaces for Computer Graphics”. HSL and HSV designed to roughly correlate with perceptual color properties while being very simple and cheap to compute.
Today HSL and HSV are most commonly used together with the sRGB color space.

One of the main advantages of HSL and HSV over the different Lab color spaces is that they map the sRGB gamut to a cylinder. This makes them easy to use since all parameters can be changed independently, without the risk of creating colors outside of the target gamut.

The main drawback on the other hand is that their properties don’t match human perception particularly well.
Reconciling these conflicting goals perfectly isn’t possible, but given that HSV and HSL don’t use anything derived from experiments relating to human perception, creating something that makes a better tradeoff does not seem unreasonable.
With this new lightness estimate, we are ready to look into the construction of Okhsv and Okhsl.

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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.
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Rec-2020 – TVs new color gamut standard used by Dolby Vision?
Read more: Rec-2020 – TVs new color gamut standard used by Dolby Vision?https://www.hdrsoft.com/resources/dri.html#bit-depth

The dynamic range is a ratio between the maximum and minimum values of a physical measurement. Its definition depends on what the dynamic range refers to.
For a scene: Dynamic range is the ratio between the brightest and darkest parts of the scene.
For a camera: Dynamic range is the ratio of saturation to noise. More specifically, the ratio of the intensity that just saturates the camera to the intensity that just lifts the camera response one standard deviation above camera noise.
For a display: Dynamic range is the ratio between the maximum and minimum intensities emitted from the screen.
The Dynamic Range of real-world scenes can be quite high — ratios of 100,000:1 are common in the natural world. An HDR (High Dynamic Range) image stores pixel values that span the whole tonal range of real-world scenes. Therefore, an HDR image is encoded in a format that allows the largest range of values, e.g. floating-point values stored with 32 bits per color channel. Another characteristics of an HDR image is that it stores linear values. This means that the value of a pixel from an HDR image is proportional to the amount of light measured by the camera.
For TVs HDR is great, but it’s not the only new TV feature worth discussing.
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LIGHTING
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Photography basics: Color Temperature and White Balance
Read more: Photography basics: Color Temperature and White BalanceColor Temperature of a light source describes the spectrum of light which is radiated from a theoretical “blackbody” (an ideal physical body that absorbs all radiation and incident light – neither reflecting it nor allowing it to pass through) with a given surface temperature.
https://en.wikipedia.org/wiki/Color_temperature
Or. Most simply it is a method of describing the color characteristics of light through a numerical value that corresponds to the color emitted by a light source, measured in degrees of Kelvin (K) on a scale from 1,000 to 10,000.
More accurately. The color temperature of a light source is the temperature of an ideal backbody that radiates light of comparable hue to that of the light source.
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Polarised vs unpolarized filtering
Read more: Polarised vs unpolarized filteringA light wave that is vibrating in more than one plane is referred to as unpolarized light. …
Polarized light waves are light waves in which the vibrations occur in a single plane. The process of transforming unpolarized light into polarized light is known as polarization.

en.wikipedia.org/wiki/Polarizing_filter_(photography)
The most common use of polarized technology is to reduce lighting complexity on the subject.
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Details such as glare and hard edges are not removed, but greatly reduced. -
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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Custom bokeh in a raytraced DOF render
Read more: Custom bokeh in a raytraced DOF renderTo achieve a custom pinhole camera effect with a custom bokeh in Arnold Raytracer, you can follow these steps:
- Set the render camera with a focal length around 50 (or as needed)
- Set the F-Stop to a high value (e.g., 22).
- Set the focus distance as you require
- Turn on DOF
- Place a plane a few cm in front of the camera.
- Texture the plane with a transparent shape at the center of it. (Transmission with no specular roughness)
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Open Source Nvidia Omniverse
Read more: Open Source Nvidia Omniverseblogs.nvidia.com/blog/2019/03/18/omniverse-collaboration-platform/
developer.nvidia.com/nvidia-omniverse
An open, Interactive 3D Design Collaboration Platform for Multi-Tool Workflows to simplify studio workflows for real-time graphics.
It supports Pixar’s Universal Scene Description technology for exchanging information about modeling, shading, animation, lighting, visual effects and rendering across multiple applications.
It also supports NVIDIA’s Material Definition Language, which allows artists to exchange information about surface materials across multiple tools.
With Omniverse, artists can see live updates made by other artists working in different applications. They can also see changes reflected in multiple tools at the same time.
For example an artist using Maya with a portal to Omniverse can collaborate with another artist using UE4 and both will see live updates of each others’ changes in their application.
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