COMPOSITION
DESIGN
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Arminas Valunas – “Coca-Cola: Wherever you are.”Read more: Arminas Valunas – “Coca-Cola: Wherever you are.”Arminas created this using Juggernaut Xl model and QR Code Monster SDXL ControlNet. 
 His pipeline:
 Static Images – Forge UI.
 Upscaled with Leonardo AI universal upscaler.
 Animated with Runway ML and Minimax.
 Video upscale – Topaz Video AI.
 Composited in Adobe Premiere.
 Juggernaut Xl download here:
 https://civitai.com/models/133005/juggernaut-xl
 QR Code Monster SDXL:
 https://civitai.com/models/197247?modelVersionId=221829
COLOR
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Stefan Ringelschwandtner – LUT Inspector toolRead more: Stefan Ringelschwandtner – LUT Inspector toolIt 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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Willem Zwarthoed – Aces gamut in VFX production pdfRead 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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StudioBinder.com – CRI color rendering indexRead more: StudioBinder.com – CRI color rendering indexwww.studiobinder.com/blog/what-is-color-rendering-index “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. ” www.pixelsham.com/2021/04/28/types-of-film-lights-and-their-efficiency 
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THOMAS MANSENCAL – The Apparent Simplicity of RGB RenderingRead more: THOMAS MANSENCAL – The Apparent Simplicity of RGB Renderinghttps://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. 
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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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Björn Ottosson – How software gets color wrongRead more: Björn Ottosson – How software gets color wronghttps://bottosson.github.io/posts/colorwrong/ Most software around us today are decent at accurately displaying colors. Processing of colors is another story unfortunately, and is often done badly. To understand what the problem is, let’s start with an example of three ways of blending green and magenta: - Perceptual blend – A smooth transition using a model designed to mimic human perception of color. The blending is done so that the perceived brightness and color varies smoothly and evenly.
- Linear blend – A model for blending color based on how light behaves physically. This type of blending can occur in many ways naturally, for example when colors are blended together by focus blur in a camera or when viewing a pattern of two colors at a distance.
- sRGB blend – This is how colors would normally be blended in computer software, using sRGB to represent the colors.
 Let’s look at some more examples of blending of colors, to see how these problems surface more practically. The examples use strong colors since then the differences are more pronounced. This is using the same three ways of blending colors as the first example. Instead of making it as easy as possible to work with color, most software make it unnecessarily hard, by doing image processing with representations not designed for it. Approximating the physical behavior of light with linear RGB models is one easy thing to do, but more work is needed to create image representations tailored for image processing and human perception. Also see: 
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The 7 key elements of brand identity design + 10 corporate identity examplesRead more: The 7 key elements of brand identity design + 10 corporate identity exampleswww.lucidpress.com/blog/the-7-key-elements-of-brand-identity-design 1. Clear brand purpose and positioning 2. Thorough market research 3. Likable brand personality 4. Memorable logo 5. Attractive color palette 6. Professional typography 7. On-brand supporting graphics 
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Tim Kang – calibrated white light values in sRGB color spaceRead more: Tim Kang – calibrated white light values in sRGB color space8bit sRGB encoded 
 2000K 255 139 22
 2700K 255 172 89
 3000K 255 184 109
 3200K 255 190 122
 4000K 255 211 165
 4300K 255 219 178
 D50 255 235 205
 D55 255 243 224
 D5600 255 244 227
 D6000 255 249 240
 D65 255 255 255
 D10000 202 221 255
 D20000 166 196 2558bit Rec709 Gamma 2.4 
 2000K 255 145 34
 2700K 255 177 97
 3000K 255 187 117
 3200K 255 193 129
 4000K 255 214 170
 4300K 255 221 182
 D50 255 236 208
 D55 255 243 226
 D5600 255 245 229
 D6000 255 250 241
 D65 255 255 255
 D10000 204 222 255
 D20000 170 199 2558bit Display P3 encoded 
 2000K 255 154 63
 2700K 255 185 109
 3000K 255 195 127
 3200K 255 201 138
 4000K 255 219 176
 4300K 255 225 187
 D50 255 239 212
 D55 255 245 228
 D5600 255 246 231
 D6000 255 251 242
 D65 255 255 255
 D10000 208 223 255
 D20000 175 199 25510bit Rec2020 PQ (100 nits) 
 2000K 520 435 273
 2700K 520 466 358
 3000K 520 475 384
 3200K 520 480 399
 4000K 520 495 446
 4300K 520 500 458
 D50 520 510 482
 D55 520 514 497
 D5600 520 514 500
 D6000 520 517 509
 D65 520 520 520
 D10000 479 489 520
 D20000 448 464 520
LIGHTING
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Black Body color aka the Planckian Locus curve for white point eye perceptionRead more: Black Body color aka the Planckian Locus curve for white point eye perceptionhttp://en.wikipedia.org/wiki/Black-body_radiation  Black-body radiation is the type of electromagnetic radiation within or surrounding a body in thermodynamic equilibrium with its environment, or emitted by a black body (an opaque and non-reflective body) held at constant, uniform temperature. The radiation has a specific spectrum and intensity that depends only on the temperature of the body. A black-body at room temperature appears black, as most of the energy it radiates is infra-red and cannot be perceived by the human eye. At higher temperatures, black bodies glow with increasing intensity and colors that range from dull red to blindingly brilliant blue-white as the temperature increases. (more…)
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Photography basics: Color Temperature and White BalanceRead 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. (more…)
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