COLOR

  • 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.

     

     

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    Read more: Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipeline
  • The Forbidden colors – Red-Green & Blue-Yellow: The Stunning Colors You Can’t See

    www.livescience.com/17948-red-green-blue-yellow-stunning-colors.html

     

     

    While the human eye has red, green, and blue-sensing cones, those cones are cross-wired in the retina to produce a luminance channel plus a red-green and a blue-yellow channel, and it’s data in that color space (known technically as “LAB”) that goes to the brain. That’s why we can’t perceive a reddish-green or a yellowish-blue, whereas such colors can be represented in the RGB color space used by digital cameras.

     

    https://en.rockcontent.com/blog/the-use-of-yellow-in-data-design

    The back of the retina is covered in light-sensitive neurons known as cone cells and rod cells. There are three types of cone cells, each sensitive to different ranges of light. These ranges overlap, but for convenience the cones are referred to as blue (short-wavelength), green (medium-wavelength), and red (long-wavelength). The rod cells are primarily used in low-light situations, so we’ll ignore those for now.

     

    When light enters the eye and hits the cone cells, the cones get excited and send signals to the brain through the visual cortex. Different wavelengths of light excite different combinations of cones to varying levels, which generates our perception of color. You can see that the red cones are most sensitive to light, and the blue cones are least sensitive. The sensitivity of green and red cones overlaps for most of the visible spectrum.

     

    Here’s how your brain takes the signals of light intensity from the cones and turns it into color information. To see red or green, your brain finds the difference between the levels of excitement in your red and green cones. This is the red-green channel.

     

    To get “brightness,” your brain combines the excitement of your red and green cones. This creates the luminance, or black-white, channel. To see yellow or blue, your brain then finds the difference between this luminance signal and the excitement of your blue cones. This is the yellow-blue channel.

     

    From the calculations made in the brain along those three channels, we get four basic colors: blue, green, yellow, and red. Seeing blue is what you experience when low-wavelength light excites the blue cones more than the green and red.

     

    Seeing green happens when light excites the green cones more than the red cones. Seeing red happens when only the red cones are excited by high-wavelength light.

     

    Here’s where it gets interesting. Seeing yellow is what happens when BOTH the green AND red cones are highly excited near their peak sensitivity. This is the biggest collective excitement that your cones ever have, aside from seeing pure white.

     

    Notice that yellow occurs at peak intensity in the graph to the right. Further, the lens and cornea of the eye happen to block shorter wavelengths, reducing sensitivity to blue and violet light.

    Read more: The Forbidden colors – Red-Green & Blue-Yellow: The Stunning Colors You Can’t See
  • What causes color

    www.webexhibits.org/causesofcolor/5.html

    Water itself has an intrinsic blue color that is a result of its molecular structure and its behavior.

    Read more: What causes color
  • sRGB vs REC709 – An introduction and FFmpeg implementations

    1. Basic Comparison

    • What they are
      • sRGB: A standard “web”/computer-display RGB color space defined by IEC 61966-2-1. It’s used for most monitors, cameras, printers, and the vast majority of images on the Internet.
      • Rec. 709: An HD-video color space defined by ITU-R BT.709. It’s the go-to standard for HDTV broadcasts, Blu-ray discs, and professional video pipelines.
    • Why they exist
      • sRGB: Ensures consistent colors across different consumer devices (PCs, phones, webcams).
      • Rec. 709: Ensures consistent colors across video production and playback chains (cameras → editing → broadcast → TV).
    • What you’ll see
      • On your desktop or phone, images tagged sRGB will look “right” without extra tweaking.
      • On an HDTV or video-editing timeline, footage tagged Rec. 709 will display accurate contrast and hue on broadcast-grade monitors.

    2. Digging Deeper

    FeaturesRGBRec. 709
    White pointD65 (6504 K), same for bothD65 (6504 K)
    Primaries (x,y)R: (0.640, 0.330) G: (0.300, 0.600) B: (0.150, 0.060)R: (0.640, 0.330) G: (0.300, 0.600) B: (0.150, 0.060)
    Gamut sizeIdentical triangle on CIE 1931 chartIdentical to sRGB
    Gamma / transferPiecewise curve: approximate 2.2 with linear toePure power-law γ≈2.4 (often approximated as 2.2 in practice)
    Matrix coefficientsN/A (pure RGB usage)Y = 0.2126 R + 0.7152 G + 0.0722 B (Rec. 709 matrix)
    Typical bit-depth8-bit/channel (with 16-bit variants)8-bit/channel (10-bit for professional video)
    Usage metadataTagged as “sRGB” in image files (PNG, JPEG, etc.)Tagged as “bt709” in video containers (MP4, MOV)
    Color rangeFull-range RGB (0–255)Studio-range Y′CbCr (Y′ [16–235], Cb/Cr [16–240])


    Why the Small Differences Matter

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    Read more: sRGB vs REC709 – An introduction and FFmpeg implementations
  • What is OLED and what can it do for your TV

    https://www.cnet.com/news/what-is-oled-and-what-can-it-do-for-your-tv/

    OLED stands for Organic Light Emitting Diode. Each pixel in an OLED display is made of a material that glows when you jab it with electricity. Kind of like the heating elements in a toaster, but with less heat and better resolution. This effect is called electroluminescence, which is one of those delightful words that is big, but actually makes sense: “electro” for electricity, “lumin” for light and “escence” for, well, basically “essence.”

    OLED TV marketing often claims “infinite” contrast ratios, and while that might sound like typical hyperbole, it’s one of the extremely rare instances where such claims are actually true. Since OLED can produce a perfect black, emitting no light whatsoever, its contrast ratio (expressed as the brightest white divided by the darkest black) is technically infinite.

    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.

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    Read more: What is OLED and what can it do for your TV
  • 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 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/

    True blue hues are rare in the natural world because synthesizing pigments that absorb longer-wavelength light (reds and yellows) while reflecting shorter-wavelength blue light requires exceptionally elaborate molecular structures—biochemical feats that most plants and animals simply don’t undertake.

    When you gaze at a blueberry’s deep blue surface, you’re actually seeing structural coloration rather than a true blue pigment. A fine, waxy bloom on the berry’s skin contains nanostructures that preferentially scatter blue and violet light, giving the fruit its signature blue sheen even though its inherent pigment is reddish.

    Similarly, many of nature’s most striking blues—like those of blue jays and morpho butterflies—arise not from blue pigments but from microscopic architectures in feathers or wing scales. These tiny ridges and air pockets manipulate incoming light so that blue wavelengths emerge most prominently, creating vivid, angle-dependent colors through scattering rather than pigment alone.

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  • Mysterious animation wins best illusion of 2011 – Motion silencing illusion

    The 2011 Best Illusion of the Year uses motion to render color changes invisible, and so reveals a quirk in our visual systems that is new to scientists.

     

    https://en.wikipedia.org/wiki/Motion_silencing_illusion

     

    “It is a really beautiful effect, revealing something about how our visual system works that we didn’t know before,” said Daniel Simons, a professor at the University of Illinois, Champaign-Urbana. Simons studies visual cognition, and did not work on this illusion. Before its creation, scientists didn’t know that motion had this effect on perception, Simons said.

    A viewer stares at a speck at the center of a ring of colored dots, which continuously change color. When the ring begins to rotate around the speck, the color changes appear to stop. But this is an illusion. For some reason, the motion causes our visual system to ignore the color changes. (You can, however, see the color changes if you follow the rotating circles with your eyes.)

     

     

     

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    Read more: Mysterious animation wins best illusion of 2011 – Motion silencing illusion

LIGHTING