COMPOSITION
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Composition – cinematography Cheat Sheet
Read 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.
What type of lighting?-> High key lighting.
Features bright, even illumination and few conspicuous shadows. This lighting key is often used in musicals and comedies.Low key lighting
Features diffused shadows and atmospheric pools of light. This lighting key is often used in mysteries and thrillers.High contrast lighting
Features harsh shafts of lights and dramatic streaks of blackness. This type of lighting is often used in tragedies and melodramas.What type of shot?
Extreme long shot
Taken from a great distance, showing much of the locale. Ifpeople are included in these shots, they usually appear as mere specks-> Long shot
Corresponds to the space between the audience and the stage in a live theater. The long shots show the characters and some of the locale.Full shot
Range with just enough space to contain the human body in full. The full shot shows the character and a minimal amount of the locale.Medium shot
Shows the human figure from the knees or waist up.Close-Up
Concentrates on a relatively small object and show very little if any locale.Extreme close-up
Focuses on an unnaturally small portion of an object, giving that part great detail and symbolic significance.What angle?
Bird’s-eye view.
The shot is photographed directly from above. This type of shot can be disorienting, and the people photographed seem insignificant.High angle.
This angle reduces the size of the objects photographed. A person photographed from this angle seems harmless and insignificant, but to a lesser extent than with the bird’s-eye view.-> Eye-level shot.
The clearest view of an object, but seldom intrinsically dramatic, because it tends to be the norm.Low angle.
This angle increases high and a sense of verticality, heightening the importance of the object photographed. A person shot from this angle is given a sense of power and respect.Oblique angle.
For this angle, the camera is tilted laterally, giving the image a slanted appearance. Oblique angles suggest tension, transition, a impending movement. They are also called canted or dutch angles.What is the dominant color?
The use of color in this shot is symbolic. The scene is set in warehouse. Both the set and characters are blues, blacks and whites.
This was intentional allowing for the scenes and shots with blood to have a great level of contrast.
What is the Lens/Filter/Stock?
Telephoto lens.
A lens that draws objects closer but also diminishes the illusion of depth.Wide-angle lens.
A lens that takes in a broad area and increases the illusion of depth but sometimes distorts the edges of the image.Fast film stock.
Highly sensitive to light, it can register an image with little illumination. However, the final product tends to be grainy.Slow film stock.
Relatively insensitive to light, it requires a great deal of illumination. The final product tends to look polished.The lens is not wide-angle because there isn’t a great sense of depth, nor are several planes in focus. The lens is probably long but not necessarily a telephoto lens because the depth isn’t inordinately compressed.
The stock is fast because of the grainy quality of the image.
Subsidiary Contrast; where does the eye go next?
The two guns.
How much visual information is packed into the image? Is the texture stark, moderate, or highly detailed?
Minimalist clutter in the warehouse allows a focus on a character driven thriller.
What is the Composition?
Horizontal.
Compositions based on horizontal lines seem visually at rest and suggest placidity or peacefulness.Vertical.
Compositions based on vertical lines seem visually at rest and suggest strength.-> Diagonal.
Compositions based on diagonal, or oblique, lines seem dynamic and suggest tension or anxiety.-> Binary. Binary structures emphasize parallelism.
Triangle.
Triadic compositions stress the dynamic interplay among three mainCircle.
Circular compositions suggest security and enclosure.Is the form open or closed? Does the image suggest a window that arbitrarily isolates a fragment of the scene? Or a proscenium arch, in which the visual elements are carefully arranged and held in balance?
The most nebulous of all the categories of mise en scene, the type of form is determined by how consciously structured the mise en scene is. Open forms stress apparently simple techniques, because with these unself-conscious methods the filmmaker is able to emphasize the immediate, the familiar, the intimate aspects of reality. In open-form images, the frame tends to be deemphasized. In closed form images, all the necessary information is carefully structured within the confines of the frame. Space seems enclosed and self-contained rather than continuous.
Could argue this is a proscenium arch because this is such a classic shot with parallels and juxtapositions.
Is the framing tight or loose? Do the character have no room to move around, or can they move freely without impediments?
Shots where the characters are placed at the edges of the frame and have little room to move around within the frame are considered tight.
Longer shots, in which characters have room to move around within the frame, are considered loose and tend to suggest freedom.
Center-framed giving us the entire scene showing isolation, place and struggle.
Depth of Field. On how many planes is the image composed (how many are in focus)? Does the background or foreground comment in any way on the mid-ground?
Standard DOF, one background and clearly defined foreground.
Which way do the characters look vis-a-vis the camera?
An actor can be photographed in any of five basic positions, each conveying different psychological overtones.
Full-front (facing the camera):
the position with the most intimacy. The character is looking in our direction, inviting our complicity.Quarter Turn:
the favored position of most filmmakers. This position offers a high degree of intimacy but with less emotional involvement than the full-front.-> Profile (looking of the frame left or right):
More remote than the quarter turn, the character in profile seems unaware of being observed, lost in his or her own thoughts.Three-quarter Turn:
More anonymous than the profile, this position is useful for conveying a character’s unfriendly or antisocial feelings, for in effect, the character is partially turning his or her back on us, rejecting our interest.Back to Camera:
The most anonymous of all positions, this position is often used to suggest a character’s alienation from the world. When a character has his or her back to the camera, we can only guess what’s taking place internally, conveying a sense of concealment, or mystery.How much space is there between the characters?
Extremely close, for a gunfight.
The way people use space can be divided into four proxemic patterns.
Intimate distances.
The intimate distance ranges from skin contact to about eighteen inches away. This is the distance of physical involvement–of love, comfort, and tenderness between individuals.-> Personal distances.
The personal distance ranges roughly from eighteen inches away to about four feet away. These distances tend to be reserved for friends and acquaintances. Personal distances preserve the privacy between individuals, yet these rages don’t necessarily suggest exclusion, as intimate distances often do.Social distances.
The social distance rages from four feet to about twelve feet. These distances are usually reserved for impersonal business and casual social gatherings. It’s a friendly range in most cases, yet somewhat more formal than the personal distance.Public distances.
The public distance extends from twelve feet to twenty-five feet or more. This range tends to be formal and rather detached.
DESIGN
COLOR
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Space bodies’ components and light spectroscopy
Read more: Space bodies’ components and light spectroscopywww.plutorules.com/page-111-space-rocks.html
This help’s us understand the composition of components in/on solar system bodies.
Dips in the observed light spectrum, also known as, lines of absorption occur as gasses absorb energy from light at specific points along the light spectrum.
These dips or darkened zones (lines of absorption) leave a finger print which identify elements and compounds.
In this image the dark absorption bands appear as lines of emission which occur as the result of emitted not reflected (absorbed) light.
Lines of absorption
Lines of emission
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Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color picking
Read more: Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color pickinghttps://bottosson.github.io/misc/colorpicker
https://bottosson.github.io/posts/colorpicker/
https://www.smashingmagazine.com/2024/10/interview-bjorn-ottosson-creator-oklab-color-space/
One problem with sRGB is that in a gradient between blue and white, it becomes a bit purple in the middle of the transition. That’s because sRGB really isn’t created to mimic how the eye sees colors; rather, it is based on how CRT monitors work. That means it works with certain frequencies of red, green, and blue, and also the non-linear coding called gamma. It’s a miracle it works as well as it does, but it’s not connected to color perception. When using those tools, you sometimes get surprising results, like purple in the gradient.
There were also attempts to create simple models matching human perception based on XYZ, but as it turned out, it’s not possible to model all color vision that way. Perception of color is incredibly complex and depends, among other things, on whether it is dark or light in the room and the background color it is against. When you look at a photograph, it also depends on what you think the color of the light source is. The dress is a typical example of color vision being very context-dependent. It is almost impossible to model this perfectly.
I based Oklab on two other color spaces, CIECAM16 and IPT. I used the lightness and saturation prediction from CIECAM16, which is a color appearance model, as a target. I actually wanted to use the datasets used to create CIECAM16, but I couldn’t find them.
IPT was designed to have better hue uniformity. In experiments, they asked people to match light and dark colors, saturated and unsaturated colors, which resulted in a dataset for which colors, subjectively, have the same hue. IPT has a few other issues but is the basis for hue in Oklab.
In the Munsell color system, colors are described with three parameters, designed to match the perceived appearance of colors: Hue, Chroma and Value. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. Modern color spaces and models, such as CIELAB, Cam16 and Björn Ottosson own Oklab, are very similar in their construction.
By far the most used color spaces today for color picking are HSL and HSV, two representations introduced in the classic 1978 paper “Color Spaces for Computer Graphics”. HSL and HSV designed to roughly correlate with perceptual color properties while being very simple and cheap to compute.
Today HSL and HSV are most commonly used together with the sRGB color space.
One of the main advantages of HSL and HSV over the different Lab color spaces is that they map the sRGB gamut to a cylinder. This makes them easy to use since all parameters can be changed independently, without the risk of creating colors outside of the target gamut.
The main drawback on the other hand is that their properties don’t match human perception particularly well.
Reconciling these conflicting goals perfectly isn’t possible, but given that HSV and HSL don’t use anything derived from experiments relating to human perception, creating something that makes a better tradeoff does not seem unreasonable.
With this new lightness estimate, we are ready to look into the construction of Okhsv and Okhsl.
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Sensitivity of human eye
Read more: Sensitivity of human eyehttp://www.wikilectures.eu/index.php/Spectral_sensitivity_of_the_human_eye
http://www.normankoren.com/Human_spectral_sensitivity_small.jpg
Spectral sensitivity of eye is influenced by light intensity. And the light intensity determines the level of activity of cones cell and rod cell. This is the main characteristic of human vision. Sensitivity to individual colors, in other words, wavelengths of the light spectrum, is explained by the RGB (red-green-blue) theory. This theory assumed that there are three kinds of cones. It’s selectively sensitive to red (700-630 nm), green (560-500 nm), and blue (490-450 nm) light. And their mutual interaction allow to perceive all colors of the spectrum.
http://weeklysciencequiz.blogspot.com/2013/01/violet-skies-are-for-birds.html
Sensitivity of human eye Sensitivity of human eyes to light increase with the decrease in light intensity. In day-light condition, the cones cell is responding to this condition. And the eye is most sensitive at 555 nm. In darkness condition, the rod cell is responding to this condition. And the eye is most sensitive at 507 nm.
As light intensity decreases, cone function changes more effective way. And when decrease the light intensity, it prompt to accumulation of rhodopsin. Furthermore, in activates rods, it allow to respond to stimuli of light in much lower intensity.
The three curves in the figure above shows the normalized response of an average human eye to various amounts of ambient light. The shift in sensitivity occurs because two types of photoreceptors called cones and rods are responsible for the eye’s response to light. The curve on the right shows the eye’s response under normal lighting conditions and this is called the photopic response. The cones respond to light under these conditions.
As mentioned previously, cones are composed of three different photo pigments that enable color perception. This curve peaks at 555 nanometers, which means that under normal lighting conditions, the eye is most sensitive to a yellowish-green color. When the light levels drop to near total darkness, the response of the eye changes significantly as shown by the scotopic response curve on the left. At this level of light, the rods are most active and the human eye is more sensitive to the light present, and less sensitive to the range of color. Rods are highly sensitive to light but are comprised of a single photo pigment, which accounts for the loss in ability to discriminate color. At this very low light level, sensitivity to blue, violet, and ultraviolet is increased, but sensitivity to yellow and red is reduced. The heavier curve in the middle represents the eye’s response at the ambient light level found in a typical inspection booth. This curve peaks at 550 nanometers, which means the eye is most sensitive to yellowish-green color at this light level. Fluorescent penetrant inspection materials are designed to fluoresce at around 550 nanometers to produce optimal sensitivity under dim lighting conditions.
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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.
Wide color gamut, or WCG, is often lumped in with HDR. While they’re often found together, they’re not intrinsically linked. Where HDR is an increase in the dynamic range of the picture (with contrast and brighter highlights in particular), a TV’s wide color gamut coverage refers to how much of the new, larger color gamuts a TV can display.
Wide color gamuts only really matter for HDR video sources like UHD Blu-rays and some streaming video, as only HDR sources are meant to take advantage of the ability to display more colors.
www.cnet.com/how-to/what-is-wide-color-gamut-wcg/
Color depth is only one aspect of color representation, expressing the precision with which the amount of each primary can be expressed through a pixel; the other aspect is how broad a range of colors can be expressed (the gamut)
Image rendering bit depth
Wide color gamuts include a greater number of colors than what most current TVs can display, so the greater a TV’s coverage of a wide color gamut, the more colors a TV will be able to reproduce.
When we talk about a color space or color gamut we refer to the range of color values stored in an image. The perception of these color also requires a display that has been tuned with to resolve these color profiles at best. This is often referred to as a ‘viewer lut’.
So this comes also usually paired with an increase in bit depth, going from the old 8 bit system (256 shades per color, with the potential of over 16.7 million colors: 256 green x 256 blue x 256 red) to 10 (1024+ shades per color, with access to over a billion colors) or higher bits, like 12 bit (4096 shades per RGB for 68 billion colors).
The advantage of higher bit depth is in the ability to bias color with the minimum loss.
For an extreme example, raising the brightness from a completely dark image allows for better reproduction, independently on the reproduction medium, due to the amount of data available at editing time:
https://www.cambridgeincolour.com/tutorials/dynamic-range.htm
https://www.hdrsoft.com/resources/dri.html#bit-depth
Note that the number of bits itself may be a misleading indication of the real dynamic range that the image reproduces — converting a Low Dynamic Range image to a higher bit depth does not change its dynamic range, of course.
- 8-bit images (i.e. 24 bits per pixel for a color image) are considered Low Dynamic Range.
- 16-bit images (i.e. 48 bits per pixel for a color image) resulting from RAW conversion are still considered Low Dynamic Range, even though the range of values they can encode is significantly higher than for 8-bit images (65536 versus 256). Note that converting a RAW file involves applying a tonal curve that compresses the dynamic range of the RAW data so that the converted image shows correctly on low dynamic range monitors. The need to adapt the output image file to the dynamic range of the display is the factor that dictates how much the dynamic range is compressed, not the output bit-depth. By using 16 instead of 8 bits, you will gain precision but you will not gain dynamic range.
- 32-bit images (i.e. 96 bits per pixel for a color image) are considered High Dynamic Range.Unlike 8- and 16-bit images which can take a finite number of values, 32-bit images are coded using floating point numbers, which means the values they can take is unlimited.It is important to note, though, that storing an image in a 32-bit HDR format is a necessary condition for an HDR image but not a sufficient one. When an image comes from a single capture with a standard camera, it will remain a Low Dynamic Range image,
Also note that bit depth and dynamic range are often confused as one, but are indeed separate concepts and there is no direct one to one relationship between them. Bit depth is about capacity, dynamic range is about the actual ratio of data stored.
The bit depth of a capturing or displaying device gives you an indication of its dynamic range capacity. That is, the highest dynamic range that the device would be capable of reproducing if all other constraints are eliminated.https://rawpedia.rawtherapee.com/Bit_Depth
Finally, note that there are two ways to “count” bits for an image — either the number of bits per color channel (BPC) or the number of bits per pixel (BPP). A bit (0,1) is the smallest unit of data stored in a computer.
For a grayscale image, 8-bit means that each pixel can be one of 256 levels of gray (256 is 2 to the power 8).
For an RGB color image, 8-bit means that each one of the three color channels can be one of 256 levels of color.
Since each pixel is represented by 3 colors in this case, 8-bit per color channel actually means 24-bit per pixel.Similarly, 16-bit for an RGB image means 65,536 levels per color channel and 48-bit per pixel.
To complicate matters, when an image is classified as 16-bit, it just means that it can store a maximum 65,535 values. It does not necessarily mean that it actually spans that range. If the camera sensors can not capture more than 12 bits of tonal values, the actual bit depth of the image will be at best 12-bit and probably less because of noise.
The following table attempts to summarize the above for the case of an RGB color image.
Type of digital support Bit depth per color channel Bit depth per pixel FStops Theoretical maximum Dynamic Range Reality 8-bit 8 24 8 256:1 most consumer images 12-bit CCD 12 36 12 4,096:1 real maximum limited by noise 14-bit CCD 14 42 14 16,384:1 real maximum limited by noise 16-bit TIFF (integer) 16 48 16 65,536:1 bit-depth in this case is not directly related to the dynamic range captured 16-bit float EXR 16 48 30 65,536:1 values are distributed more closely in the (lower) darker tones than in the (higher) lighter ones, thus allowing for a more accurate description of the tones more significant to humans. The range of normalized 16-bit floats can represent thirty stops of information with 1024 steps per stop. We have eighteen and a half stops over middle gray, and eleven and a half below. The denormalized numbers provide an additional ten stops with decreasing precision per stop.
http://download.nvidia.com/developer/GPU_Gems/CD_Image/Image_Processing/OpenEXR/OpenEXR-1.0.6/doc/#recsHDR image (e.g. Radiance format) 32 96 “infinite” 4.3 billion:1 real maximum limited by the captured dynamic range 32-bit floats are often called “single-precision” floats, and 64-bit floats are often called “double-precision” floats. 16-bit floats therefore are called “half-precision” floats, or just “half floats”.
https://petapixel.com/2018/09/19/8-12-14-vs-16-bit-depth-what-do-you-really-need
On a separate note, even Photoshop does not handle 16bit per channel. Photoshop does actually use 16-bits per channel. However, it treats the 16th digit differently – it is simply added to the value created from the first 15-digits. This is sometimes called 15+1 bits. This means that instead of 216 possible values (which would be 65,536 possible values) there are only 215+1 possible values (which is 32,768 +1 = 32,769 possible values).
Rec-601 (for the older SDTV format, very similar to rec-709) and Rec-709 (the HDTV’s recommended set of color standards, at times also referred to sRGB, although not exactly the same) are currently the most spread color formats and hardware configurations in the world.
Following those you can find the larger P3 gamut, more commonly used in theaters and in digital production houses (with small variations and improvements to color coverage), as well as most of best 4K/WCG TVs.
And a new standard is now promoted against P3, referred to Rec-2020 and UHDTV.
It is still debatable if this is going to be adopted at consumer level beyond the P3, mainly due to lack of hardware supporting it. But initial tests do prove that it would be a future proof investment.
www.colour-science.org/anders-langlands/
Rec. 2020 is ultimately designed for television, and not cinema. Therefore, it is to be expected that its properties must behave according to current signal processing standards. In this respect, its foundation is based on current HD and SD video signal characteristics.
As far as color bit depth is concerned, it allows for a maximum of 12 bits, which is more than enough for humans.
Comparing standards, REC-709 covers 35.9% of the human visible spectrum. P3 45.5%. And REC-2020 75.8%.
https://www.avsforum.com/forum/166-lcd-flat-panel-displays/2812161-what-color-volume.htmlComparing coverage to hardware devices
To note that all the new standards generally score very high on the Pointer’s Gamut chart. But with REC-2020 scoring 99.9% vs P3 at 88.2%.
www.tftcentral.co.uk/articles/pointers_gamut.htmhttps://www.slideshare.net/hpduiker/acescg-a-common-color-encoding-for-visual-effects-applications
The Pointer’s gamut is (an approximation of) the gamut of real surface colors as can be seen by the human eye, based on the research by Michael R. Pointer (1980). What this means is that every color that can be reflected by the surface of an object of any material is inside the Pointer’s gamut. Basically establishing a widely respected target for color reproduction. Visually, Pointers Gamut represents the colors we see about us in the natural world. Colors outside Pointers Gamut include those that do not occur naturally, such as neon lights and computer-generated colors possible in animation. Which would partially be accounted for with the new gamuts.
cinepedia.com/picture/color-gamut/
Not all current TVs can support the full spread of the new gamuts. Here is a list of modern TVs’ color coverage in percentage:
www.rtings.com/tv/tests/picture-quality/wide-color-gamut-rec-709-dci-p3-rec-2020There are no TVs that can come close to displaying all the colors within Rec.2020, and there likely won’t be for at least a few years. However, to help future-proof the technology, Rec.2020 support is already baked into the HDR spec. That means that the same genuine HDR media that fills the DCI P3 space on a compatible TV now, will in a few years also fill Rec.2020 on a TV supporting that larger space.
Rec.2020’s main gains are in the number of new tones of green that it will display, though it also offers improvements to the number of blue and red colors as well. Altogether, Rec.2020 will cover about 75% of the visual spectrum, which is a sizeable increase in coverage even over DCI P3.
Dolby Vision
https://www.highdefdigest.com/news/show/what-is-dolby-vision/39049
https://www.techhive.com/article/3237232/dolby-vision-vs-hdr10-which-is-best.html
Dolby Vision is a proprietary end-to-end High Dynamic Range (HDR) format that covers content creation and playback through select cinemas, Ultra HD displays, and 4K titles. Like other HDR standards, the process uses expanded brightness to improve contrast between dark and light aspects of an image, bringing out deeper black levels and more realistic details in specular highlights — like the sun reflecting off of an ocean — in specially graded Dolby Vision material.
The iPhone 12 Pro gets the ability to record 4K 10-bit HDR video. According to Apple, it is the very first smartphone that is capable of capturing Dolby Vision HDR.
The iPhone 12 Pro takes two separate exposures and runs them through Apple’s custom image signal processor to create a histogram, which is a graph of the tonal values in each frame. The Dolby Vision metadata is then generated based on that histogram. In Laymen’s terms, it is essentially doing real-time grading while you are shooting. This is only possible due to the A14 Bionic chip.
Dolby Vision also allows for 12-bit color, as opposed to HDR10’s and HDR10+’s 10-bit color. While no retail TV we’re aware of supports 12-bit color, Dolby claims it can be down-sampled in such a way as to render 10-bit color more accurately.
Resources for more reading:
https://www.avsforum.com/forum/166-lcd-flat-panel-displays/2812161-what-color-volume.html
wolfcrow.com/say-hello-to-rec-2020-the-color-space-of-the-future/
www.cnet.com/news/ultra-hd-tv-color-part-ii-the-future/
LIGHTING
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Capturing the world in HDR for real time projects – Call of Duty: Advanced Warfare
Read more: Capturing the world in HDR for real time projects – Call of Duty: Advanced WarfareReal-World Measurements for Call of Duty: Advanced Warfare
www.activision.com/cdn/research/Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf
Local version
Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf
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Gamma correction
Read 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.Our eyes, different camera or video recorder devices do not correctly capture luminance. (they are not linear)
Different display devices (monitor, phone screen, TV) do not display luminance correctly neither. So, one needs to correct them, therefore the gamma correction function.The human perception of brightness, under common illumination conditions (not pitch black nor blindingly bright), follows an approximate power function (note: no relation to the gamma function), with greater sensitivity to relative differences between darker tones than between lighter ones, consistent with the Stevens’ power law for brightness perception. If images are not gamma-encoded, they allocate too many bits or too much bandwidth to highlights that humans cannot differentiate, and too few bits or too little bandwidth to shadow values that humans are sensitive to and would require more bits/bandwidth to maintain the same visual quality.
https://blog.amerlux.com/4-things-architects-should-know-about-lumens-vs-perceived-brightness/
cones manage color receptivity, rods determine how large our pupils should be. The larger (more dilated) our pupils are, the more light enters our eyes. In dark situations, our rods dilate our pupils so we can see better. This impacts how we perceive brightness.
https://www.cambridgeincolour.com/tutorials/gamma-correction.htm
A gamma encoded image has to have “gamma correction” applied when it is viewed — which effectively converts it back into light from the original scene. In other words, the purpose of gamma encoding is for recording the image — not for displaying the image. Fortunately this second step (the “display gamma”) is automatically performed by your monitor and video card. The following diagram illustrates how all of this fits together:
Display gamma
The display gamma can be a little confusing because this term is often used interchangeably with gamma correction, since it corrects for the file gamma. This is the gamma that you are controlling when you perform monitor calibration and adjust your contrast setting. Fortunately, the industry has converged on a standard display gamma of 2.2, so one doesn’t need to worry about the pros/cons of different values.Gamma encoding of images is used to optimize the usage of bits when encoding an image, or bandwidth used to transport an image, by taking advantage of the non-linear manner in which humans perceive light and color. Human response to luminance is also biased. Especially sensible to dark areas.
Thus, the human visual system has a non-linear response to the power of the incoming light, so a fixed increase in power will not have a fixed increase in perceived brightness.
We perceive a value as half bright when it is actually 18% of the original intensity not 50%. As such, our perception is not linear.You probably already know that a pixel can have any ‘value’ of Red, Green, and Blue between 0 and 255, and you would therefore think that a pixel value of 127 would appear as half of the maximum possible brightness, and that a value of 64 would represent one-quarter brightness, and so on. Well, that’s just not the case.
Pixar Color Management
https://renderman.pixar.com/color-management
– Why do we need linear gamma?
Because light works linearly and therefore only works properly when it lights linear values.– Why do we need to view in sRGB?
Because the resulting linear image in not suitable for viewing, but contains all the proper data. Pixar’s IT viewer can compensate by showing the rendered image through a sRGB look up table (LUT), which is identical to what will be the final image after the sRGB gamma curve is applied in post.This would be simple enough if every software would play by the same rules, but they don’t. In fact, the default gamma workflow for many 3D software is incorrect. This is where the knowledge of a proper imaging workflow comes in to save the day.
Cathode-ray tubes have a peculiar relationship between the voltage applied to them, and the amount of light emitted. It isn’t linear, and in fact it follows what’s called by mathematicians and other geeks, a ‘power law’ (a number raised to a power). The numerical value of that power is what we call the gamma of the monitor or system.
Thus. Gamma describes the nonlinear relationship between the pixel levels in your computer and the luminance of your monitor (the light energy it emits) or the reflectance of your prints. The equation is,
Luminance = C * value^gamma + black level
– C is set by the monitor Contrast control.
– Value is the pixel level normalized to a maximum of 1. For an 8 bit monitor with pixel levels 0 – 255, value = (pixel level)/255.
– Black level is set by the (misnamed) monitor Brightness control. The relationship is linear if gamma = 1. The chart illustrates the relationship for gamma = 1, 1.5, 1.8 and 2.2 with C = 1 and black level = 0.
Gamma affects middle tones; it has no effect on black or white. If gamma is set too high, middle tones appear too dark. Conversely, if it’s set too low, middle tones appear too light.
The native gamma of monitors – the relationship between grid voltage and luminance – is typically around 2.5, though it can vary considerably. This is well above any of the display standards, so you must be aware of gamma and correct it.
A display gamma of 2.2 is the de facto standard for the Windows operating system and the Internet-standard sRGB color space.
The old standard for Mcintosh and prepress file interchange is 1.8. It is now 2.2 as well.
Video cameras have gammas of approximately 0.45 – the inverse of 2.2. The viewing or system gamma is the product of the gammas of all the devices in the system – the image acquisition device (film+scanner or digital camera), color lookup table (LUT), and monitor. System gamma is typically between 1.1 and 1.5. Viewing flare and other factor make images look flat at system gamma = 1.0.
Most laptop LCD screens are poorly suited for critical image editing because gamma is extremely sensitive to viewing angle.
More about screens
https://www.cambridgeincolour.com/tutorials/gamma-correction.htm
CRT Monitors. Due to an odd bit of engineering luck, the native gamma of a CRT is 2.5 — almost the inverse of our eyes. Values from a gamma-encoded file could therefore be sent straight to the screen and they would automatically be corrected and appear nearly OK. However, a small gamma correction of ~1/1.1 needs to be applied to achieve an overall display gamma of 2.2. This is usually already set by the manufacturer’s default settings, but can also be set during monitor calibration.
LCD Monitors. LCD monitors weren’t so fortunate; ensuring an overall display gamma of 2.2 often requires substantial corrections, and they are also much less consistent than CRT’s. LCDs therefore require something called a look-up table (LUT) in order to ensure that input values are depicted using the intended display gamma (amongst other things). See the tutorial on monitor calibration: look-up tables for more on this topic.
About black level (brightness). Your monitor’s brightness control (which should actually be called black level) can be adjusted using the mostly black pattern on the right side of the chart. This pattern contains two dark gray vertical bars, A and B, which increase in luminance with increasing gamma. (If you can’t see them, your black level is way low.) The left bar (A) should be just above the threshold of visibility opposite your chosen gamma (2.2 or 1.8) – it should be invisible where gamma is lower by about 0.3. The right bar (B) should be distinctly visible: brighter than (A), but still very dark. This chart is only for monitors; it doesn’t work on printed media.
The 1.8 and 2.2 gray patterns at the bottom of the image represent a test of monitor quality and calibration. If your monitor is functioning properly and calibrated to gamma = 2.2 or 1.8, the corresponding pattern will appear smooth neutral gray when viewed from a distance. Any waviness, irregularity, or color banding indicates incorrect monitor calibration or poor performance.
Another test to see whether one’s computer monitor is properly hardware adjusted and can display shadow detail in sRGB images properly, they should see the left half of the circle in the large black square very faintly but the right half should be clearly visible. If not, one can adjust their monitor’s contrast and/or brightness setting. This alters the monitor’s perceived gamma. The image is best viewed against a black background.
This procedure is not suitable for calibrating or print-proofing a monitor. It can be useful for making a monitor display sRGB images approximately correctly, on systems in which profiles are not used (for example, the Firefox browser prior to version 3.0 and many others) or in systems that assume untagged source images are in the sRGB colorspace.
On some operating systems running the X Window System, one can set the gamma correction factor (applied to the existing gamma value) by issuing the command xgamma -gamma 0.9 for setting gamma correction factor to 0.9, and xgamma for querying current value of that factor (the default is 1.0). In OS X systems, the gamma and other related screen calibrations are made through the System Preference
https://www.kinematicsoup.com/news/2016/6/15/gamma-and-linear-space-what-they-are-how-they-differ
Linear color space means that numerical intensity values correspond proportionally to their perceived intensity. This means that the colors can be added and multiplied correctly. A color space without that property is called ”non-linear”. Below is an example where an intensity value is doubled in a linear and a non-linear color space. While the corresponding numerical values in linear space are correct, in the non-linear space (gamma = 0.45, more on this later) we can’t simply double the value to get the correct intensity.
The need for gamma arises for two main reasons: The first is that screens have been built with a non-linear response to intensity. The other is that the human eye can tell the difference between darker shades better than lighter shades. This means that when images are compressed to save space, we want to have greater accuracy for dark intensities at the expense of lighter intensities. Both of these problems are resolved using gamma correction, which is to say the intensity of every pixel in an image is put through a power function. Specifically, gamma is the name given to the power applied to the image.
CRT screens, simply by how they work, apply a gamma of around 2.2, and modern LCD screens are designed to mimic that behavior. A gamma of 2.2, the reciprocal of 0.45, when applied to the brightened images will darken them, leaving the original image.
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