COMPOSITION
DESIGN
COLOR
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Scientists claim to have discovered ‘new colour’ no one has seen before: Olo
Read more: Scientists claim to have discovered ‘new colour’ no one has seen before: Olohttps://www.bbc.com/news/articles/clyq0n3em41o
By stimulating specific cells in the retina, the participants claim to have witnessed a blue-green colour that scientists have called “olo”, but some experts have said the existence of a new colour is “open to argument”.
The findings, published in the journal Science Advances on Friday, have been described by the study’s co-author, Prof Ren Ng from the University of California, as “remarkable”.
(A) System inputs. (i) Retina map of 103 cone cells preclassified by spectral type (7). (ii) Target visual percept (here, a video of a child, see movie S1 at 1:04). (iii) Infrared cellular-scale imaging of the retina with 60-frames-per-second rolling shutter. Fixational eye movement is visible over the three frames shown.
(B) System outputs. (iv) Real-time per-cone target activation levels to reproduce the target percept, computed by: extracting eye motion from the input video relative to the retina map; identifying the spectral type of every cone in the field of view; computing the per-cone activation the target percept would have produced. (v) Intensities of visible-wavelength 488-nm laser microdoses at each cone required to achieve its target activation level.
(C) Infrared imaging and visible-wavelength stimulation are physically accomplished in a raster scan across the retinal region using AOSLO. By modulating the visible-wavelength beam’s intensity, the laser microdoses shown in (v) are delivered. Drawing adapted with permission [Harmening and Sincich (54)].
(D) Examples of target percepts with corresponding cone activations and laser microdoses, ranging from colored squares to complex imagery. Teal-striped regions represent the color “olo” of stimulating only M cones.
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Light and Matter : The 2018 theory of Physically-Based Rendering and Shading by Allegorithmic
Read more: Light and Matter : The 2018 theory of Physically-Based Rendering and Shading by Allegorithmicacademy.substance3d.com/courses/the-pbr-guide-part-1
academy.substance3d.com/courses/the-pbr-guide-part-2
Local copy:
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Akiyoshi Kitaoka – Surround biased illumination perception
Read more: Akiyoshi Kitaoka – Surround biased illumination perceptionhttps://x.com/AkiyoshiKitaoka/status/1798705648001327209
The left face appears whitish and the right one blackish, but they are made up of the same luminance.
https://community.wolfram.com/groups/-/m/t/3191015
Illusory staircase Gelb effect
https://www.psy.ritsumei.ac.jp/akitaoka/illgelbe.html
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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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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.
LIGHTING
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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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What is the Light Field?
Read more: What is the Light Field?http://lightfield-forum.com/what-is-the-lightfield/
The light field consists of the total of all light rays in 3D space, flowing through every point and in every direction.
How to Record a Light Field
- a single, robotically controlled camera
- a rotating arc of cameras
- an array of cameras or camera modules
- a single camera or camera lens fitted with a microlens array
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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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Types of Film Lights and their efficiency – CRI, Color Temperature and Luminous Efficacy
Read more: Types of Film Lights and their efficiency – CRI, Color Temperature and Luminous Efficacynofilmschool.com/types-of-film-lights
“Not every light performs the same way. Lights and lighting are tricky to handle. You have to plan for every circumstance. But the good news is, lighting can be adjusted. Let’s look at different factors that affect lighting in every scene you shoot. “
Use CRI, Luminous Efficacy and color temperature controls to match your needs.
Color Temperature
Color temperature describes the “color” of white light by a light source radiated by a perfect black body at a given temperature measured in degrees Kelvinhttps://www.pixelsham.com/2019/10/18/color-temperature/
CRI
“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. “https://www.studiobinder.com/blog/what-is-color-rendering-index
(more…)
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