COMPOSITION
DESIGN
COLOR
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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.
(more…) -
Christopher Butler – Understanding the Eye-Mind Connection – Vision is a mental process
Read more: Christopher Butler – Understanding the Eye-Mind Connection – Vision is a mental processhttps://www.chrbutler.com/understanding-the-eye-mind-connection
The intricate relationship between the eyes and the brain, often termed the eye-mind connection, reveals that vision is predominantly a cognitive process. This understanding has profound implications for fields such as design, where capturing and maintaining attention is paramount. This essay delves into the nuances of visual perception, the brain’s role in interpreting visual data, and how this knowledge can be applied to effective design strategies.
This cognitive aspect of vision is evident in phenomena such as optical illusions, where the brain interprets visual information in a way that contradicts physical reality. These illusions underscore that what we “see” is not merely a direct recording of the external world but a constructed experience shaped by cognitive processes.
Understanding the cognitive nature of vision is crucial for effective design. Designers must consider how the brain processes visual information to create compelling and engaging visuals. This involves several key principles:
- Attention and Engagement
- Visual Hierarchy
- Cognitive Load Management
- Context and Meaning
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Victor Perez – The Color Management Handbook for Visual Effects Artists
Read more: Victor Perez – The Color Management Handbook for Visual Effects ArtistsDigital Color Principles, Color Management Fundamentals & ACES Workflows
LIGHTING
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IES Light Profiles and editing software
Read more: IES Light Profiles and editing softwarehttp://www.derekjenson.com/3d-blog/ies-light-profiles
https://ieslibrary.com/en/browse#ies
https://leomoon.com/store/shaders/ies-lights-pack
https://docs.arnoldrenderer.com/display/a5afmug/ai+photometric+light
IES profiles are useful for creating life-like lighting, as they can represent the physical distribution of light from any light source.
The IES format was created by the Illumination Engineering Society, and most lighting manufacturers provide IES profile for the lights they manufacture.
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Convert between light exposure and intensity
import math,sys def Exposure2Intensity(exposure): exp = float(exposure) result = math.pow(2,exp) print(result) Exposure2Intensity(0) def Intensity2Exposure(intensity): inarg = float(intensity) if inarg == 0: print("Exposure of zero intensity is undefined.") return if inarg < 1e-323: inarg = max(inarg, 1e-323) print("Exposure of negative intensities is undefined. Clamping to a very small value instead (1e-323)") result = math.log(inarg, 2) print(result) Intensity2Exposure(0.1)
Why Exposure?
Exposure is a stop value that multiplies the intensity by 2 to the power of the stop. Increasing exposure by 1 results in double the amount of light.
Artists think in “stops.” Doubling or halving brightness is easy math and common in grading and look-dev.
Exposure counts doublings in whole stops:- +1 stop = ×2 brightness
- −1 stop = ×0.5 brightness
This gives perceptually even controls across both bright and dark values.
Why Intensity?
Intensity is linear.
It’s what render engines and compositors expect when:- Summing values
- Averaging pixels
- Multiplying or filtering pixel data
Use intensity when you need the actual math on pixel/light data.
Formulas (from your Python)
- Intensity from exposure: intensity = 2**exposure
- Exposure from intensity: exposure = log₂(intensity)
Guardrails:
- Intensity must be > 0 to compute exposure.
- If intensity = 0 → exposure is undefined.
- Clamp tiny values (e.g.
1e−323
) before using log₂.
Use Exposure (stops) when…
- You want artist-friendly sliders (−5…+5 stops)
- Adjusting look-dev or grading in even stops
- Matching plates with quick ±1 stop tweaks
- Tweening brightness changes smoothly across ranges
Use Intensity (linear) when…
- Storing raw pixel/light values
- Multiplying textures or lights by a gain
- Performing sums, averages, and filters
- Feeding values to render engines expecting linear data
Examples
- +2 stops → 2**2 = 4.0 (×4)
- +1 stop → 2**1 = 2.0 (×2)
- 0 stop → 2**0 = 1.0 (×1)
- −1 stop → 2**(−1) = 0.5 (×0.5)
- −2 stops → 2**(−2) = 0.25 (×0.25)
- Intensity 0.1 → exposure = log₂(0.1) ≈ −3.32
Rule of thumb
Think in stops (exposure) for controls and matching.
Compute in linear (intensity) for rendering and math. -
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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