COMPOSITION
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Composition – cinematography Cheat SheetRead 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.
 (more…)
 What type of lighting?
DESIGN
COLOR
LIGHTING
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3D Lighting Tutorial by Amaan KramRead more: 3D Lighting Tutorial by Amaan Kramhttp://www.amaanakram.com/lightingT/part1.htm The goals of lighting in 3D computer graphics are more or less the same as those of real world lighting. Lighting serves a basic function of bringing out, or pushing back the shapes of objects visible from the camera’s view. 
 It gives a two-dimensional image on the monitor an illusion of the third dimension-depth.But it does not just stop there. It gives an image its personality, its character. A scene lit in different ways can give a feeling of happiness, of sorrow, of fear etc., and it can do so in dramatic or subtle ways. Along with personality and character, lighting fills a scene with emotion that is directly transmitted to the viewer. Trying to simulate a real environment in an artificial one can be a daunting task. But even if you make your 3D rendering look absolutely photo-realistic, it doesn’t guarantee that the image carries enough emotion to elicit a “wow” from the people viewing it. Making 3D renderings photo-realistic can be hard. Putting deep emotions in them can be even harder. However, if you plan out your lighting strategy for the mood and emotion that you want your rendering to express, you make the process easier for yourself. Each light source can be broken down in to 4 distinct components and analyzed accordingly. · Intensity 
 · Direction
 · Color
 · SizeThe overall thrust of this writing is to produce photo-realistic images by applying good lighting techniques. 
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Convert between light exposure and intensityRead more: Convert between light exposure and intensityimport 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 thumbThink in stops (exposure) for controls and matching. 
 Compute in linear (intensity) for rendering and math.
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Vahan Sosoyan MakeHDR – an OpenFX open source plug-in for merging multiple LDR images into a single HDRIRead more: Vahan Sosoyan MakeHDR – an OpenFX open source plug-in for merging multiple LDR images into a single HDRIhttps://github.com/Sosoyan/make-hdr Feature notes- Merge up to 16 inputs with 8, 10 or 12 bit depth processing
- User friendly logarithmic Tone Mapping controls within the tool
- Advanced controls such as Sampling rate and Smoothness
 Available at cross platform on Linux, MacOS and Windows Works consistent in compositing applications like Nuke, Fusion, Natron. NOTE: The goal is to clean the initial individual brackets before or at merging time as much as possible. 
 This means:- keeping original shooting metadata
- de-fringing
- removing aberration (through camera lens data or automatically)
- at 32 bit
- in ACEScg (or ACES) wherever possible
  
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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. (more…)
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