COLOR

  • Yasuharu YOSHIZAWA – Comparison of sRGB vs ACREScg in Nuke

    Answering the question that is often asked, “Do I need to use ACEScg to display an sRGB monitor in the end?” (Demonstration shown at an in-house seminar)
    Comparison of scanlineRender output with extreme color lights on color charts with sRGB/ACREScg in color – OCIO -working space in Nuke

    Download the Nuke script:

    Read more: Yasuharu YOSHIZAWA – Comparison of sRGB vs ACREScg in Nuke
  • Anders Langlands – Render Color Spaces

    https://www.colour-science.org/anders-langlands/

     

    This page compares images rendered in Arnold using spectral rendering and different sets of colourspace primaries: Rec.709, Rec.2020, ACES and DCI-P3. The SPD data for the GretagMacbeth Color Checker are the measurements of Noburu Ohta, taken from Mansencal, Mauderer and Parsons (2014) colour-science.org.

     

    ,
    Read more: Anders Langlands – Render Color Spaces
  • Scientists claim to have discovered ‘new colour’ no one has seen before: Olo

    https://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.

    Read more: Scientists claim to have discovered ‘new colour’ no one has seen before: Olo
  • The Color of Infinite Temperature

    This is the color of something infinitely hot.

    Of course you’d instantly be fried by gamma rays of arbitrarily high frequency, but this would be its spectrum in the visible range.

    johncarlosbaez.wordpress.com/2022/01/16/the-color-of-infinite-temperature/

    This is also the color of a typical neutron star. They’re so hot they look the same.
    It’s also the color of the early Universe!

    This was worked out by David Madore.

    The color he got is sRGB(148,177,255).
    www.htmlcsscolor.com/hex/94B1FF

    And according to the experts who sip latte all day and make up names for colors, this color is called ‘Perano’.

    ,
    Read more: The Color of Infinite Temperature
  • Tim Kang – calibrated white light values in sRGB color space

    https://www.linkedin.com/posts/timkang_colorimetry-cinematography-nerdalert-activity-7058330978007584769-9xln

     

    8bit 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 166 196 255

    8bit 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 170 199 255

    8bit 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 175 199 255

    10bit 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

     

    ,
    Read more: Tim Kang – calibrated white light values in sRGB color space
  • 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

    (more…)

    , ,
    Read more: What Is The Resolution and view coverage Of The human Eye. And what distance is TV at best?
  • Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipeline

    https://jo.dreggn.org/home/2018_manuka.pdf

     

    http://www.fxguide.com/featured/manuka-weta-digitals-new-renderer/

     

    The Manuka rendering architecture has been designed in the spirit of the classic reyes rendering architecture. In its core, reyes is based on stochastic rasterisation of micropolygons, facilitating depth of field, motion blur, high geometric complexity,and programmable shading.

     

    This is commonly achieved with Monte Carlo path tracing, using a paradigm often called shade-on-hit, in which the renderer alternates tracing rays with running shaders on the various ray hits. The shaders take the role of generating the inputs of the local material structure which is then used bypath sampling logic to evaluate contributions and to inform what further rays to cast through the scene.

     

    Over the years, however, the expectations have risen substantially when it comes to image quality. Computing pictures which are indistinguishable from real footage requires accurate simulation of light transport, which is most often performed using some variant of Monte Carlo path tracing. Unfortunately this paradigm requires random memory accesses to the whole scene and does not lend itself well to a rasterisation approach at all.

     

    Manuka is both a uni-directional and bidirectional path tracer and encompasses multiple importance sampling (MIS). Interestingly, and importantly for production character skin work, it is the first major production renderer to incorporate spectral MIS in the form of a new ‘Hero Spectral Sampling’ technique, which was recently published at Eurographics Symposium on Rendering 2014.

     

    Manuka propose a shade-before-hit paradigm in-stead and minimise I/O strain (and some memory costs) on the system, leveraging locality of reference by running pattern generation shaders before we execute light transport simulation by path sampling, “compressing” any bvh structure as needed, and as such also limiting duplication of source data.
    The difference with reyes is that instead of baking colors into the geometry like in Reyes, manuka bakes surface closures. This means that light transport is still calculated with path tracing, but all texture lookups etc. are done up-front and baked into the geometry.

     

    The main drawback with this method is that geometry has to be tessellated to its highest, stable topology before shading can be evaluated properly. As such, the high cost to first pixel. Even a basic 4 vertices square becomes a much more complex model with this approach.

     

     

    Manuka use the RenderMan Shading Language (rsl) for programmable shading [Pixar Animation Studios 2015], but we do not invoke rsl shaders when intersecting a ray with a surface (often called shade-on-hit). Instead, we pre-tessellate and pre-shade all the input geometry in the front end of the renderer.
    This way, we can efficiently order shading computations to sup-port near-optimal texture locality, vectorisation, and parallelism. This system avoids repeated evaluation of shaders at the same surface point, and presents a minimal amount of memory to be accessed during light transport time. An added benefit is that the acceleration structure for ray tracing (abounding volume hierarchy, bvh) is built once on the final tessellated geometry, which allows us to ray trace more efficiently than multi-level bvhs and avoids costly caching of on-demand tessellated micropolygons and the associated scheduling issues.

     

    For the shading reasons above, in terms of AOVs, the studio approach is to succeed at combining complex shading with ray paths in the render rather than pass a multi-pass render to compositing.

     

    For the Spectral Rendering component. The light transport stage is fully spectral, using a continuously sampled wavelength which is traced with each path and used to apply the spectral camera sensitivity of the sensor. This allows for faithfully support any degree of observer metamerism as the camera footage they are intended to match as well as complex materials which require wavelength dependent phenomena such as diffraction, dispersion, interference, iridescence, or chromatic extinction and Rayleigh scattering in participating media.

     

    As opposed to the original reyes paper, we use bilinear interpolation of these bsdf inputs later when evaluating bsdfs per pathv ertex during light transport4. This improves temporal stability of geometry which moves very slowly with respect to the pixel raster

     

    In terms of the pipeline, everything rendered at Weta was already completely interwoven with their deep data pipeline. Manuka very much was written with deep data in mind. Here, Manuka not so much extends the deep capabilities, rather it fully matches the already extremely complex and powerful setup Weta Digital already enjoy with RenderMan. For example, an ape in a scene can be selected, its ID is available and a NUKE artist can then paint in 3D say a hand and part of the way up the neutral posed ape.

     

    We called our system Manuka, as a respectful nod to reyes: we had heard a story froma former ILM employee about how reyes got its name from how fond the early Pixar people were of their lunches at Point Reyes, and decided to name our system after our surrounding natural environment, too. Manuka is a kind of tea tree very common in New Zealand which has very many very small leaves, in analogy to micropolygons ina tree structure for ray tracing. It also happens to be the case that Weta Digital’s main site is on Manuka Street.

     

     

    , ,
    Read more: Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipeline
  • No one could see the colour blue until modern times

    https://www.businessinsider.com/what-is-blue-and-how-do-we-see-color-2015-2

    The way that humans see the world… until we have a way to describe something, even something so fundamental as a colour, we may not even notice that something it’s there.

     

    Ancient languages didn’t have a word for blue — not Greek, not Chinese, not Japanese, not Hebrew, not Icelandic cultures. And without a word for the colour, there’s evidence that they may not have seen it at all.

    https://www.wnycstudios.org/story/211119-colors

     

    Every language first had a word for black and for white, or dark and light. The next word for a colour to come into existence — in every language studied around the world — was red, the colour of blood and wine.

    After red, historically, yellow appears, and later, green (though in a couple of languages, yellow and green switch places). The last of these colours to appear in every language is blue.

     

    The only ancient culture to develop a word for blue was the Egyptians — and as it happens, they were also the only culture that had a way to produce a blue dye.

    https://mymodernmet.com/shades-of-blue-color-history/



    https://www.msn.com/en-us/news/technology/scientists-recreate-lost-recipes-for-a-5-000-year-old-egyptian-blue-dye/ar-AA1FXcj1

    Assessment of process variability and color in synthesized and ancient Egyptian blue pigments | npj Heritage Science

    The approximately 5,000-year-old dye wasn’t a single color, but instead encompassed a range of hues, from deep blues to duller grays and greens. Artisans first crafted Egyptian blue during the Fourth Dynasty (roughly 2613 to 2494 BCE) from recipes reliant on calcium-copper silicate. These techniques were later adopted by Romans in lieu of more expensive materials like lapis lazuli and turquoise. But the additional ingredient lists were lost to history by the time of the Renaissance. 

    McCloy’s team confirmed that cuprorivaite—the naturally occurring mineral equivalent to Egyptian blue—remains the primary color influence in each hue. Despite the presence of other components, Egyptian blue appears as a uniform color after the cuprorivaite becomes encased in colorless particles such as silicate during the heating process.

     

    Considered to be the first ever synthetically produced color pigment, Egyptian blue (also known as cuprorivaite) was created around 2,200 B.C. It was made from ground limestone mixed with sand and a copper-containing mineral, such as azurite or malachite, which was then heated between 1470 and 1650°F. The result was an opaque blue glass which then had to be crushed and combined with thickening agents such as egg whites to create a long-lasting paint or glaze.

     

     

    If you think about it, blue doesn’t appear much in nature — there aren’t animals with blue pigments (except for one butterfly, Obrina Olivewing, all animals generate blue through light scattering), blue eyes are rare (also blue through light scattering), and blue flowers are mostly human creations. There is, of course, the sky, but is that really blue?

     

     

    So before we had a word for it, did people not naturally see blue? Do you really see something if you don’t have a word for it?

     

    A researcher named Jules Davidoff traveled to Namibia to investigate this, where he conducted an experiment with the Himba tribe, who speak a language that has no word for blue or distinction between blue and green. When shown a circle with 11 green squares and one blue, they couldn’t pick out which one was different from the others.

     

    When looking at a circle of green squares with only one slightly different shade, they could immediately spot the different one. Can you?

     

    Davidoff says that without a word for a colour, without a way of identifying it as different, it’s much harder for us to notice what’s unique about it — even though our eyes are physically seeing the blocks it in the same way.

     

    Further research brought to wider discussions about color perception in humans. Everything that we make is based on the fact that humans are trichromatic. The television only has 3 colors. Our color printers have 3 different colors. But some people, and in specific some women seemed to be more sensible to color differences… mainly because they’re just more aware or – because of the job that they do.

    Eventually this brought to the discovery of a small percentage of the population, referred to as tetrachromats, which developed an extra cone sensitivity to yellow, likely due to gene modifications.

    The interesting detail about these is that even between tetrachromats, only the ones that had a reason to develop, label and work with extra color sensitivity actually developed the ability to use their native skills.

     

    So before blue became a common concept, maybe humans saw it. But it seems they didn’t know they were seeing it.

    If you see something yet can’t see it, does it exist? Did colours come into existence over time? Not technically, but our ability to notice them… may have…

     

    , , ,
    Read more: No one could see the colour blue until modern times

LIGHTING


| Featured AI
| Design And Composition
| Explore posts


unreal | pipeline | virtual production | free | learn | photoshop | 360 | macro | google | nvidia | resolution | open source | hdri | real-time | photography basics | nuke




Subscribe to PixelSham.com RSS for free
Subscribe to PixelSham.com RSS for free