COMPOSITION
DESIGN
COLOR
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Stefan Ringelschwandtner – LUT Inspector tool
It lets you load any .cube LUT right in your browser, see the RGB curves, and use a split view on the Granger Test Image to compare the original vs. LUT-applied version in real time — perfect for spotting hue shifts, saturation changes, and contrast tweaks.
https://mononodes.com/lut-inspector/
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Thomas Mansencal – Colour Science for Python
Read more: Thomas Mansencal – Colour Science for Pythonhttps://thomasmansencal.substack.com/p/colour-science-for-python
https://www.colour-science.org/
Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science. It is freely available under the BSD-3-Clause terms.
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Victor Perez – ACES Color Management in DaVinci Resolve
Read more: Victor Perez – ACES Color Management in DaVinci Resolvehttpv://www.youtube.com/watch?v=i–TS88-6xA
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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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Is it possible to get a dark yellow
Read more: Is it possible to get a dark yellowhttps://www.patreon.com/posts/102660674
https://www.linkedin.com/posts/stephenwestland_here-is-a-post-about-the-dark-yellow-problem-activity-7187131643764092929-7uCL
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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.
LIGHTING
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Debayer – A free command line tool to convert camera raw images into scene-linear exr
https://github.com/jedypod/debayer
The only required dependency is oiiotool. However other “debayer engines” are also supported.
- OpenImageIO – oiiotool is used for converting debayered tif images to exr.
- Debayer Engines
- RawTherapee – Powerful raw development software used to decode raw images. High quality, good selection of debayer algorithms, and more advanced raw processing like chromatic aberration removal.
- LibRaw – dcraw_emu commandline utility included with LibRaw. Optional alternative for debayer. Simple, fast and effective.
- Darktable – Uses darktable-cli plus an xmp config to process.
- vkdt – uses vkdt-cli to debayer. Pretty experimental still. Uses Vulkan for image processing. Stupidly fast. Pretty limited.
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Photography basics: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs Illuminance
Read more: Photography basics: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs Illuminancehttps://www.translatorscafe.com/unit-converter/en-US/illumination/1-11/
The power output of a light source is measured using the unit of watts W. This is a direct measure to calculate how much power the light is going to drain from your socket and it is not relatable to the light brightness itself.
The amount of energy emitted from it per second. That energy comes out in a form of photons which we can crudely represent with rays of light coming out of the source. The higher the power the more rays emitted from the source in a unit of time.
Not all energy emitted is visible to the human eye, so we often rely on photometric measurements, which takes in account the sensitivity of human eye to different wavelenghts
Details in the post
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HDRI Median Cut plugin
www.hdrlabs.com/picturenaut/plugins.html
Note. The Median Cut algorithm is typically used for color quantization, which involves reducing the number of colors in an image while preserving its visual quality. It doesn’t directly provide a way to identify the brightest areas in an image. However, if you’re interested in identifying the brightest areas, you might want to look into other methods like thresholding, histogram analysis, or edge detection, through openCV for example.
Here is an openCV example:
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Simulon – a Hollywood production studio app in the hands of an independent creator with access to consumer hardware, LDRi to HDRi through ML
Divesh Naidoo: The video below was made with a live in-camera preview and auto-exposure matching, no camera solve, no HDRI capture and no manual compositing setup. Using the new Simulon phone app.
LDR to HDR through ML
https://simulon.typeform.com/betatest
Process example
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HDRI shooting and editing by Xuan Prada and Greg Zaal
www.xuanprada.com/blog/2014/11/3/hdri-shooting
http://blog.gregzaal.com/2016/03/16/make-your-own-hdri/
http://blog.hdrihaven.com/how-to-create-high-quality-hdri/
Shooting checklist
- Full coverage of the scene (fish-eye shots)
- Backplates for look-development (including ground or floor)
- Macbeth chart for white balance
- Grey ball for lighting calibration
- Chrome ball for lighting orientation
- Basic scene measurements
- Material samples
- Individual HDR artificial lighting sources if required
Methodology
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