COMPOSITION
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Mastering Camera Shots and Angles: A Guide for FilmmakersRead more: Mastering Camera Shots and Angles: A Guide for Filmmakershttps://website.ltx.studio/blog/mastering-camera-shots-and-angles 1. Extreme Wide Shot  2. Wide Shot  3. Medium Shot  4. Close Up  5. Extreme Close Up  
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Photography basics: Camera Aspect Ratio, Sensor Size and Depth of Field – resolutionsRead more: Photography basics: Camera Aspect Ratio, Sensor Size and Depth of Field – resolutionshttp://www.shutterangle.com/2012/cinematic-look-aspect-ratio-sensor-size-depth-of-field/ http://www.shutterangle.com/2012/film-video-aspect-ratio-artistic-choice/ 
DESIGN
COLOR
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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.
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 What type of lighting?
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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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What Is The Resolution and view coverage Of The human Eye. And what distance is TV at best?Read more: What Is The Resolution and view coverage Of The human Eye. And what distance is TV at best?https://www.discovery.com/science/mexapixels-in-human-eye About 576 megapixels for the entire field of view. Consider a view in front of you that is 90 degrees by 90 degrees, like looking through an open window at a scene. The number of pixels would be: 
 90 degrees * 60 arc-minutes/degree * 1/0.3 * 90 * 60 * 1/0.3 = 324,000,000 pixels (324 megapixels).At any one moment, you actually do not perceive that many pixels, but your eye moves around the scene to see all the detail you want. But the human eye really sees a larger field of view, close to 180 degrees. Let’s be conservative and use 120 degrees for the field of view. Then we would see: 120 * 120 * 60 * 60 / (0.3 * 0.3) = 576 megapixels. Or. 7 megapixels for the 2 degree focus arc… + 1 megapixel for the rest. https://clarkvision.com/articles/eye-resolution.html Details in the post 
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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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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
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mmColorTarget – Nuke Gizmo for color matching a MacBeth chartRead more: mmColorTarget – Nuke Gizmo for color matching a MacBeth charthttps://www.marcomeyer-vfx.de/posts/2014-04-11-mmcolortarget-nuke-gizmo/ https://www.marcomeyer-vfx.de/posts/mmcolortarget-nuke-gizmo/ https://vimeo.com/9.1652466e+07 https://www.nukepedia.com/gizmos/colour/mmcolortarget 
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Pattern generatorsRead more: Pattern generatorshttp://qrohlf.com/trianglify-generator/ https://halftonepro.com/app/polygons# https://mattdesl.svbtle.com/generative-art-with-nodejs-and-canvas https://www.patterncooler.com/ http://permadi.com/java/spaint/spaint.html https://dribbble.com/shots/1847313-Kaleidoscope-Generator-PSD http://eskimoblood.github.io/gerstnerizer/ http://www.stripegenerator.com/ http://btmills.github.io/geopattern/geopattern.html http://fractalarchitect.net/FA4-Random-Generator.html https://sciencevsmagic.net/fractal/#0605,0000,3,2,0,1,2 https://sites.google.com/site/mandelbulber/home 
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Gamma correctionRead more: Gamma correction http://www.normankoren.com/makingfineprints1A.html#Gammabox https://en.wikipedia.org/wiki/Gamma_correction http://www.photoscientia.co.uk/Gamma.htm https://www.w3.org/Graphics/Color/sRGB.html http://www.eizoglobal.com/library/basics/lcd_display_gamma/index.html https://forum.reallusion.com/PrintTopic308094.aspx Basically, gamma is the relationship between the brightness of a pixel as it appears on the screen, and the numerical value of that pixel. Generally Gamma is just about defining relationships. Three main types: 
 – Image Gamma encoded in images
 – Display Gammas encoded in hardware and/or viewing time
 – System or Viewing Gamma which is the net effect of all gammas when you look back at a final image. In theory this should flatten back to 1.0 gamma.
 (more…)
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OLED vs QLED – What TV is better?Read more: OLED vs QLED – What TV is better?Supported by LG, Philips, Panasonic and Sony sell the OLED system TVs. 
 OLED stands for “organic light emitting diode.”
 It is a fundamentally different technology from LCD, the major type of TV today.
 OLED is “emissive,” meaning the pixels emit their own light.Samsung is branding its best TVs with a new acronym: “QLED” 
 QLED (according to Samsung) stands for “quantum dot LED TV.”
 It is a variation of the common LED LCD, adding a quantum dot film to the LCD “sandwich.”
 QLED, like LCD, is, in its current form, “transmissive” and relies on an LED backlight.OLED is the only technology capable of absolute blacks and extremely bright whites on a per-pixel basis. LCD definitely can’t do that, and even the vaunted, beloved, dearly departed plasma couldn’t do absolute blacks. QLED, as an improvement over OLED, significantly improves the picture quality. QLED can produce an even wider range of colors than OLED, which says something about this new tech. QLED is also known to produce up to 40% higher luminance efficiency than OLED technology. Further, many tests conclude that QLED is far more efficient in terms of power consumption than its predecessor, OLED. 
 (more…)
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RawTherapee – a free, open source, cross-platform raw image and HDRi processing programRead more: RawTherapee – a free, open source, cross-platform raw image and HDRi processing program5.10 of this tool includes excellent tools to clean up cr2 and cr3 used on set to support HDRI processing. 
 Converting raw to AcesCG 32 bit tiffs with metadata.
LIGHTING
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HDRI ResourcesRead more: HDRI ResourcesText2Light - https://www.cgtrader.com/free-3d-models/exterior/other/10-free-hdr-panoramas-created-with-text2light-zero-shot
- https://frozenburning.github.io/projects/text2light/
- https://github.com/FrozenBurning/Text2Light
 Royalty free links - https://locationtextures.com/panoramas/
- http://www.noahwitchell.com/freebies
- https://polyhaven.com/hdris
- https://hdrmaps.com/
- https://www.ihdri.com/
- https://hdrihaven.com/
- https://www.domeble.com/
- http://www.hdrlabs.com/sibl/archive.html
- https://www.hdri-hub.com/hdrishop/hdri
- http://noemotionhdrs.net/hdrevening.html
- https://www.openfootage.net/hdri-panorama/
- https://www.zwischendrin.com/en/browse/hdri
 Nvidia GauGAN360 
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Magnific.ai Relight – change the entire lighting of a sceneRead more: Magnific.ai Relight – change the entire lighting of a sceneIt’s a new Magnific spell that allows you to change the entire lighting of a scene and, optionally, the background with just: 1/ A prompt OR 
 2/ A reference image OR
 3/ A light map (drawing your own lights)https://x.com/javilopen/status/1805274155065176489 
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Insta360-Research-Team DiT360 – High-Fidelity Panoramic Image Generation via Hybrid TrainingRead more: Insta360-Research-Team DiT360 – High-Fidelity Panoramic Image Generation via Hybrid Traininghttps://github.com/Insta360-Research-Team/DiT360 DiT360 is a framework for high-quality panoramic image generation, leveraging both perspective and panoramic data in a hybrid training scheme. It adopts a two-level strategy—image-level cross-domain guidance and token-level hybrid supervision—to enhance perceptual realism and geometric fidelity.  
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