COMPOSITION
DESIGN
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Cosmic Motors book by Daniel Simon
http://danielsimon.com/cosmic-motors-the-book/
Book Cover Cosmic Motors, Copyright by Cosmic Motors LLC / Daniel Simon www.danielsimon.com -
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This legendary DC Comics style guide was nearly lost for years – now you can buy it
Read more: This legendary DC Comics style guide was nearly lost for years – now you can buy ithttps://www.fastcompany.com/91133306/dc-comics-style-guide-was-lost-for-years-now-you-can-buy-it
Reproduced from a rare original copy, the book features over 165 highly-detailed scans of the legendary art by José Luis García-López, with an introduction by Paul Levitz, former president of DC Comics.
https://standardsmanual.com/products/1982-dc-comics-style-guide
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Mike Mitchell x Marvel x Mondo – Iconic portraits of Marvel’s huge stable of heroes and villains
Read more: Mike Mitchell x Marvel x Mondo – Iconic portraits of Marvel’s huge stable of heroes and villainshttps://mondoshop.com/blogs/gallery/16910155-mike-mitchell-x-marvel-x-mondo
https://time.com/69659/marvel-comics-mike-mitchell-artist-portraits/
COLOR
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Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipeline
Read more: Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipelinehttps://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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FXGuide – ACES 2.0 with ILM’s Alex Fry
https://draftdocs.acescentral.com/background/whats-new/
ACES 2.0 is the second major release of the components that make up the ACES system. The most significant change is a new suite of rendering transforms whose design was informed by collected feedback and requests from users of ACES 1. The changes aim to improve the appearance of perceived artifacts and to complete previously unfinished components of the system, resulting in a more complete, robust, and consistent product.
Highlights of the key changes in ACES 2.0 are as follows:
- New output transforms, including:
- A less aggressive tone scale
- More intuitive controls to create custom outputs to non-standard displays
- Robust gamut mapping to improve perceptual uniformity
- Improved performance of the inverse transforms
- Enhanced AMF specification
- An updated specification for ACES Transform IDs
- OpenEXR compression recommendations
- Enhanced tools for generating Input Transforms and recommended procedures for characterizing prosumer cameras
- Look Transform Library
- Expanded documentation
Rendering Transform
The most substantial change in ACES 2.0 is a complete redesign of the rendering transform.
ACES 2.0 was built as a unified system, rather than through piecemeal additions. Different deliverable outputs “match” better and making outputs to display setups other than the provided presets is intended to be user-driven. The rendering transforms are less likely to produce undesirable artifacts “out of the box”, which means less time can be spent fixing problematic images and more time making pictures look the way you want.
Key design goals
- Improve consistency of tone scale and provide an easy to use parameter to allow for outputs between preset dynamic ranges
- Minimize hue skews across exposure range in a region of same hue
- Unify for structural consistency across transform type
- Easy to use parameters to create outputs other than the presets
- Robust gamut mapping to improve harsh clipping artifacts
- Fill extents of output code value cube (where appropriate and expected)
- Invertible – not necessarily reversible, but Output > ACES > Output round-trip should be possible
- Accomplish all of the above while maintaining an acceptable “out-of-the box” rendering
- New output transforms, including:
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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.
When analyzing TVs color, it may be beneficial to consider at least 3 elements:
“Color Depth”, “Color Gamut”, and “Dynamic Range”.Color Depth (or “Bit-Depth”, e.g. 8-bit, 10-bit, 12-bit) determines how many distinct color variations (tones/shades) can be viewed on a given display.
Color Gamut (e.g. WCG) determines which specific colors can be displayed from a given “Color Space” (Rec.709, Rec.2020, DCI-P3) (i.e. the color range).
Dynamic Range (SDR, HDR) determines the luminosity range of a specific color – from its darkest shade (or tone) to its brightest.
The overall brightness range of a color will be determined by a display’s “contrast ratio”, that is, the ratio of luminance between the darkest black that can be produced and the brightest white.
Color Volume is the “Color Gamut” + the “Dynamic/Luminosity Range”.
A TV’s Color Volume will not only determine which specific colors can be displayed (the color range) but also that color’s luminosity range, which will have an affect on its “brightness”, and “colorfulness” (intensity and saturation).The better the colour volume in a TV, the closer to life the colours appear.
QLED TV can express nearly all of the colours in the DCI-P3 colour space, and of those colours, express 100% of the colour volume, thereby producing an incredible range of colours.
With OLED TV, when the image is too bright, the percentage of the colours in the colour volume produced by the TV drops significantly. The colours get washed out and can only express around 70% colour volume, making the picture quality drop too.
Note. OLED TV uses organic material, so it may lose colour expression as it ages.
Resources for more reading and comparison below
www.avsforum.com/forum/166-lcd-flat-panel-displays/2812161-what-color-volume.html
www.newtechnologytv.com/qled-vs-oled/
news.samsung.com/za/qled-tv-vs-oled-tv
www.cnet.com/news/qled-vs-oled-samsungs-tv-tech-and-lgs-tv-tech-are-not-the-same/
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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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Is it possible to get a dark yellow
Read more: Is it possible to get a dark yellowhttps://www.patreon.com/posts/102660674
https://www.linkedin.com/posts/stephenwestland_here-is-a-post-about-the-dark-yellow-problem-activity-7187131643764092929-7uCL
LIGHTING
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Cinematographers Blueprint 300dpi poster
Read more: Cinematographers Blueprint 300dpi posterThe 300dpi digital poster is now available to all PixelSham.com subscribers.
If you have already subscribed and wish a copy, please send me a note through the contact page.
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IES Light Profiles and editing software
Read more: IES Light Profiles and editing softwarehttp://www.derekjenson.com/3d-blog/ies-light-profiles
https://ieslibrary.com/en/browse#ies
https://leomoon.com/store/shaders/ies-lights-pack
https://docs.arnoldrenderer.com/display/a5afmug/ai+photometric+light
IES profiles are useful for creating life-like lighting, as they can represent the physical distribution of light from any light source.
The IES format was created by the Illumination Engineering Society, and most lighting manufacturers provide IES profile for the lights they manufacture.
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Photography basics: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs Illuminance
Read more: Photography basics: Lumens vs Candelas (candle) vs Lux vs FootCandle vs Watts vs Irradiance vs Illuminancehttps://www.translatorscafe.com/unit-converter/en-US/illumination/1-11/
The power output of a light source is measured using the unit of watts W. This is a direct measure to calculate how much power the light is going to drain from your socket and it is not relatable to the light brightness itself.
The amount of energy emitted from it per second. That energy comes out in a form of photons which we can crudely represent with rays of light coming out of the source. The higher the power the more rays emitted from the source in a unit of time.
Not all energy emitted is visible to the human eye, so we often rely on photometric measurements, which takes in account the sensitivity of human eye to different wavelenghts
Details in the post
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HDRI Median Cut plugin
www.hdrlabs.com/picturenaut/plugins.html
Note. The Median Cut algorithm is typically used for color quantization, which involves reducing the number of colors in an image while preserving its visual quality. It doesn’t directly provide a way to identify the brightest areas in an image. However, if you’re interested in identifying the brightest areas, you might want to look into other methods like thresholding, histogram analysis, or edge detection, through openCV for example.
Here is an openCV example:
# bottom left coordinates = 0,0 import numpy as np import cv2 # Load the HDR or EXR image image = cv2.imread('your_image_path.exr', cv2.IMREAD_UNCHANGED) # Load as-is without modification # Calculate the luminance from the HDR channels (assuming RGB format) luminance = np.dot(image[..., :3], [0.299, 0.587, 0.114]) # Set a threshold value based on estimated EV threshold_value = 2.4 # Estimated threshold value based on 4.8 EV # Apply the threshold to identify bright areas # The
luminance
array contains the calculated luminance values for each pixel in the image. # Thethreshold_value
is a user-defined value that represents a cutoff point, separating "bright" and "dark" areas in terms of perceived luminance.thresholded = (luminance > threshold_value) * 255 # Convert the thresholded image to uint8 for contour detection thresholded = thresholded.astype(np.uint8) # Find contours of the bright areas contours, _ = cv2.findContours(thresholded, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # Create a list to store the bounding boxes of bright areas bright_areas = [] # Iterate through contours and extract bounding boxes for contour in contours: x, y, w, h = cv2.boundingRect(contour) # Adjust y-coordinate based on bottom-left origin y_bottom_left_origin = image.shape[0] - (y + h) bright_areas.append((x, y_bottom_left_origin, x + w, y_bottom_left_origin + h)) # Store as (x1, y1, x2, y2) # Print the identified bright areas print("Bright Areas (x1, y1, x2, y2):") for area in bright_areas: print(area)
More details
Luminance and Exposure in an EXR Image:
- An EXR (Extended Dynamic Range) image format is often used to store high dynamic range (HDR) images that contain a wide range of luminance values, capturing both dark and bright areas.
- Luminance refers to the perceived brightness of a pixel in an image. In an RGB image, luminance is often calculated using a weighted sum of the red, green, and blue channels, where different weights are assigned to each channel to account for human perception.
- In an EXR image, the pixel values can represent radiometrically accurate scene values, including actual radiance or irradiance levels. These values are directly related to the amount of light emitted or reflected by objects in the scene.
The luminance line is calculating the luminance of each pixel in the image using a weighted sum of the red, green, and blue channels. The three float values [0.299, 0.587, 0.114] are the weights used to perform this calculation.
These weights are based on the concept of luminosity, which aims to approximate the perceived brightness of a color by taking into account the human eye’s sensitivity to different colors. The values are often derived from the NTSC (National Television System Committee) standard, which is used in various color image processing operations.
Here’s the breakdown of the float values:
- 0.299: Weight for the red channel.
- 0.587: Weight for the green channel.
- 0.114: Weight for the blue channel.
The weighted sum of these channels helps create a grayscale image where the pixel values represent the perceived brightness. This technique is often used when converting a color image to grayscale or when calculating luminance for certain operations, as it takes into account the human eye’s sensitivity to different colors.
For the threshold, remember that the exact relationship between EV values and pixel values can depend on the tone-mapping or normalization applied to the HDR image, as well as the dynamic range of the image itself.
To establish a relationship between exposure and the threshold value, you can consider the relationship between linear and logarithmic scales:
- Linear and Logarithmic Scales:
- Exposure values in an EXR image are often represented in logarithmic scales, such as EV (exposure value). Each increment in EV represents a doubling or halving of the amount of light captured.
- Threshold values for luminance thresholding are usually linear, representing an actual luminance level.
- Conversion Between Scales:
- To establish a mathematical relationship, you need to convert between the logarithmic exposure scale and the linear threshold scale.
- One common method is to use a power function. For instance, you can use a power function to convert EV to a linear intensity value.
threshold_value = base_value * (2 ** EV)
Here,
EV
is the exposure value,base_value
is a scaling factor that determines the relationship between EV and threshold_value, and2 ** EV
is used to convert the logarithmic EV to a linear intensity value. - Choosing the Base Value:
- The
base_value
factor should be determined based on the dynamic range of your EXR image and the specific luminance values you are dealing with. - You may need to experiment with different values of
base_value
to achieve the desired separation of bright areas from the rest of the image.
- The
Let’s say you have an EXR image with a dynamic range of 12 EV, which is a common range for many high dynamic range images. In this case, you want to set a threshold value that corresponds to a certain number of EV above the middle gray level (which is often considered to be around 0.18).
Here’s an example of how you might determine a
base_value
to achieve this:# Define the dynamic range of the image in EV dynamic_range = 12 # Choose the desired number of EV above middle gray for thresholding desired_ev_above_middle_gray = 2 # Calculate the threshold value based on the desired EV above middle gray threshold_value = 0.18 * (2 ** (desired_ev_above_middle_gray / dynamic_range)) print("Threshold Value:", threshold_value)
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NVidia DiffusionRenderer – Neural Inverse and Forward Rendering with Video Diffusion Models. How NVIDIA reimagined relighting
https://www.fxguide.com/quicktakes/diffusing-reality-how-nvidia-reimagined-relighting/
https://research.nvidia.com/labs/toronto-ai/DiffusionRenderer/
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Polarised vs unpolarized filtering
A light wave that is vibrating in more than one plane is referred to as unpolarized light. …
Polarized light waves are light waves in which the vibrations occur in a single plane. The process of transforming unpolarized light into polarized light is known as polarization.
en.wikipedia.org/wiki/Polarizing_filter_(photography)
The most common use of polarized technology is to reduce lighting complexity on the subject.
Details such as glare and hard edges are not removed, but greatly reduced.This method is usually used in VFX to capture raw images with the least amount of specular diffusion or pollution, thus allowing artists to infer detail back through typical shading and rendering techniques and on demand.
Light reflected from a non-metallic surface becomes polarized; this effect is maximum at Brewster’s angle, about 56° from the vertical for common glass.
A polarizer rotated to pass only light polarized in the direction perpendicular to the reflected light will absorb much of it. This absorption allows glare reflected from, for example, a body of water or a road to be reduced. Reflections from shiny surfaces (e.g. vegetation, sweaty skin, water surfaces, glass) are also reduced. This allows the natural color and detail of what is beneath to come through. Reflections from a window into a dark interior can be much reduced, allowing it to be seen through. (The same effects are available for vision by using polarizing sunglasses.)
www.physicsclassroom.com/class/light/u12l1e.cfm
Some of the light coming from the sky is polarized (bees use this phenomenon for navigation). The electrons in the air molecules cause a scattering of sunlight in all directions. This explains why the sky is not dark during the day. But when looked at from the sides, the light emitted from a specific electron is totally polarized.[3] Hence, a picture taken in a direction at 90 degrees from the sun can take advantage of this polarization.
Use of a polarizing filter, in the correct direction, will filter out the polarized component of skylight, darkening the sky; the landscape below it, and clouds, will be less affected, giving a photograph with a darker and more dramatic sky, and emphasizing the clouds.
There are two types of polarizing filters readily available, linear and “circular”, which have exactly the same effect photographically. But the metering and auto-focus sensors in certain cameras, including virtually all auto-focus SLRs, will not work properly with linear polarizers because the beam splitters used to split off the light for focusing and metering are polarization-dependent.
Polarizing filters reduce the light passed through to the film or sensor by about one to three stops (2–8×) depending on how much of the light is polarized at the filter angle selected. Auto-exposure cameras will adjust for this by widening the aperture, lengthening the time the shutter is open, and/or increasing the ASA/ISO speed of the camera.
www.adorama.com/alc/nd-filter-vs-polarizer-what%25e2%2580%2599s-the-difference
Neutral Density (ND) filters help control image exposure by reducing the light that enters the camera so that you can have more control of your depth of field and shutter speed. Polarizers or polarizing filters work in a similar way, but the difference is that they selectively let light waves of a certain polarization pass through. This effect helps create more vivid colors in an image, as well as manage glare and reflections from water surfaces. Both are regarded as some of the best filters for landscape and travel photography as they reduce the dynamic range in high-contrast images, thus enabling photographers to capture more realistic and dramatic sceneries.
shopfelixgray.com/blog/polarized-vs-non-polarized-sunglasses/
www.eyebuydirect.com/blog/difference-polarized-nonpolarized-sunglasses/
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