COLOR

  • THOMAS MANSENCAL – The Apparent Simplicity of RGB Rendering

     

    https://thomasmansencal.substack.com/p/the-apparent-simplicity-of-rgb-rendering

     

    The primary goal of physically-based rendering (PBR) is to create a simulation that accurately reproduces the imaging process of electro-magnetic spectrum radiation incident to an observer. This simulation should be indistinguishable from reality for a similar observer.

     

    Because a camera is not sensitive to incident light the same way than a human observer, the images it captures are transformed to be colorimetric. A project might require infrared imaging simulation, a portion of the electro-magnetic spectrum that is invisible to us. Radically different observers might image the same scene but the act of observing does not change the intrinsic properties of the objects being imaged. Consequently, the physical modelling of the virtual scene should be independent of the observer.

    Read more: THOMAS MANSENCAL – The Apparent Simplicity of RGB Rendering
  • 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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    Read more: Gamma correction
  • 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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    Read more: OLED vs QLED – What TV is better?

LIGHTING

  • Photography basics: Exposure Value vs Photographic Exposure vs Il/Luminance vs Pixel luminance measurements

    Also see: https://www.pixelsham.com/2015/05/16/how-aperture-shutter-speed-and-iso-affect-your-photos/

     

    In photography, exposure value (EV) is a number that represents a combination of a camera’s shutter speed and f-number, such that all combinations that yield the same exposure have the same EV (for any fixed scene luminance).

     

     

    The EV concept was developed in an attempt to simplify choosing among combinations of equivalent camera settings. Although all camera settings with the same EV nominally give the same exposure, they do not necessarily give the same picture. EV is also used to indicate an interval on the photographic exposure scale. 1 EV corresponding to a standard power-of-2 exposure step, commonly referred to as a stop

     

    EV 0 corresponds to an exposure time of 1 sec and a relative aperture of f/1.0. If the EV is known, it can be used to select combinations of exposure time and f-number.

     

    https://www.streetdirectory.com/travel_guide/141307/photography/exposure_value_ev_and_exposure_compensation.html

    Note EV does not equal to photographic exposure. Photographic Exposure is defined as how much light hits the camera’s sensor. It depends on the camera settings mainly aperture and shutter speed. Exposure value (known as EV) is a number that represents the exposure setting of the camera.

     

    Thus, strictly, EV is not a measure of luminance (indirect or reflected exposure) or illuminance (incidental exposure); rather, an EV corresponds to a luminance (or illuminance) for which a camera with a given ISO speed would use the indicated EV to obtain the nominally correct exposure. Nonetheless, it is common practice among photographic equipment manufacturers to express luminance in EV for ISO 100 speed, as when specifying metering range or autofocus sensitivity.

     

    The exposure depends on two things: how much light gets through the lenses to the camera’s sensor and for how long the sensor is exposed. The former is a function of the aperture value while the latter is a function of the shutter speed. Exposure value is a number that represents this potential amount of light that could hit the sensor. It is important to understand that exposure value is a measure of how exposed the sensor is to light and not a measure of how much light actually hits the sensor. The exposure value is independent of how lit the scene is. For example a pair of aperture value and shutter speed represents the same exposure value both if the camera is used during a very bright day or during a dark night.

     

    Each exposure value number represents all the possible shutter and aperture settings that result in the same exposure. Although the exposure value is the same for different combinations of aperture values and shutter speeds the resulting photo can be very different (the aperture controls the depth of field while shutter speed controls how much motion is captured).

    EV 0.0 is defined as the exposure when setting the aperture to f-number 1.0 and the shutter speed to 1 second. All other exposure values are relative to that number. Exposure values are on a base two logarithmic scale. This means that every single step of EV – plus or minus 1 – represents the exposure (actual light that hits the sensor) being halved or doubled.

    https://www.streetdirectory.com/travel_guide/141307/photography/exposure_value_ev_and_exposure_compensation.html

     

    Formula

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

     

    https://www.scantips.com/lights/math.html

     

    which means   2EV = N² / t

    where

    • N is the relative aperture (f-number) Important: Note that f/stop values must first be squared in most calculations
    • t is the exposure time (shutter speed) in seconds

    EV 0 corresponds to an exposure time of 1 sec and an aperture of f/1.0.

    Example: If f/16 and 1/4 second, then this is:

    (N² / t) = (16 × 16 ÷ 1/4) = (16 × 16 × 4) = 1024.

    Log₂(1024) is EV 10. Meaning, 210 = 1024.

     

    Collecting photographic exposure using Light Meters

    https://photo.stackexchange.com/questions/968/how-can-i-correctly-measure-light-using-a-built-in-camera-meter

    The exposure meter in the camera does not know whether the subject itself is bright or not. It simply measures the amount of light that comes in, and makes a guess based on that. The camera will aim for 18% gray, meaning if you take a photo of an entirely white surface, and an entirely black surface you should get two identical images which both are gray (at least in theory)

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

    For reflected-light meters, camera settings are related to ISO speed and subject luminance by the reflected-light exposure equation:

    where

    • N is the relative aperture (f-number)
    • t is the exposure time (“shutter speed”) in seconds
    • L is the average scene luminance
    • S is the ISO arithmetic speed
    • K is the reflected-light meter calibration constant

     

    For incident-light meters, camera settings are related to ISO speed and subject illuminance by the incident-light exposure equation:

    where

    • E is the illuminance (in lux)
    • C is the incident-light meter calibration constant

     

    Two values for K are in common use: 12.5 (Canon, Nikon, and Sekonic) and 14 (Minolta, Kenko, and Pentax); the difference between the two values is approximately 1/6 EV.
    For C a value of 250 is commonly used.

     

    Nonetheless, it is common practice among photographic equipment manufacturers to also express luminance in EV for ISO 100 speed. Using K = 12.5, the relationship between EV at ISO 100 and luminance L is then :

    L = 2(EV-3)

     

    The situation with incident-light meters is more complicated than that for reflected-light meters, because the calibration constant C depends on the sensor type. Illuminance is measured with a flat sensor; a typical value for C is 250 with illuminance in lux. Using C = 250, the relationship between EV at ISO 100 and illuminance E is then :

     

    E = 2.5 * 2(EV)

     

    https://nofilmschool.com/2018/03/want-easier-and-faster-way-calculate-exposure-formula

    Three basic factors go into the exposure formula itself instead: aperture, shutter, and ISO. Plus a light meter calibration constant.

    f-stop²/shutter (in seconds) = lux * ISO/C

     

    If you at least know four of those variables, you’ll be able to calculate the missing value.

    So, say you want to figure out how much light you’re going to need in order to shoot at a certain f-stop. Well, all you do is plug in your values (you should know the f-stop, ISO, and your light meter calibration constant) into the formula below:

    lux = C (f-stop²/shutter (in seconds))/ISO

     

    Exposure Value Calculator:

    https://snapheadshots.com/resources/exposure-and-light-calculator

     

    https://www.scantips.com/lights/exposurecalc.html

     

    https://www.pointsinfocus.com/tools/exposure-settings-ev-calculator/#google_vignette

     

    From that perspective, an exposure stop is a measurement of Exposure and provides a universal linear scale to measure the increase and decrease in light, exposed to the image sensor, due to changes in shutter speed, iso & f-stop.
    +-1 stop is a doubling or halving of the amount of light let in when taking a photo.
    1 EV is just another way to say one stop of exposure change.

     

    One major use of EV (Exposure Value) is just to measure any change of exposure, where one EV implies a change of one stop of exposure. Like when we compensate our picture in the camera.

     

    If the picture comes out too dark, our manual exposure could correct the next one by directly adjusting one of the three exposure controls (f/stop, shutter speed, or ISO). Or if using camera automation, the camera meter is controlling it, but we might apply +1 EV exposure compensation (or +1 EV flash compensation) to make the result goal brighter, as desired. This use of 1 EV is just another way to say one stop of exposure change.

     

    On a perfect day the difference from sampling the sky vs the sun exposure with diffusing spot meters is about 3.2 exposure difference.

     ~15.4 EV for the sun
     ~12.2 EV for the sky
    

    That is as a ballpark. All still influenced by surroundings, accuracy parameters, fov of the sensor…

     

     

     

    EV calculator

    https://www.scantips.com/lights/evchart.html#calc

    http://www.fredparker.com/ultexp1.htm

     

    Exposure value is basically used to indicate an interval on the photographic exposure scale, with a difference of 1 EV corresponding to a standard power-of-2 exposure step, also commonly referred to as a “stop”.

     

    https://contrastly.com/a-guide-to-understanding-exposure-value-ev/

     

    Retrieving photographic exposure from an image

    All you can hope to measure with your camera and some images is the relative reflected luminance. Even if you have the camera settings. https://en.wikipedia.org/wiki/Relative_luminance

     

    If you REALLY want to know the amount of light in absolute radiometric units, you’re going to need to use some kind of absolute light meter or measured light source to calibrate your camera. For references on how to do this, see: Section 2.5 Obtaining Absolute Radiance from http://www.pauldebevec.com/Research/HDR/debevec-siggraph97.pdf

     

    IF you are still trying to gauge relative brightness, the level of the sun in Nuke can vary, but it should be in the thousands. Ie: between 30,000 and 65,0000 rgb value depending on time of the day, season and atmospherics.

     

    The values for a 12 o’clock sun, with the sun sampled at EV 15.5 (shutter 1/30, ISO 100, F22) is 32.000 RGB max values (or 32,000 pixel luminance).
    The thing to keep an eye for is the level of contrast between sunny side/fill side.  The terminator should be quite obvious,  there can be up to 3 stops difference between fill/key in sunny lit objects.

     

    Note: In Foundry’s Nuke, the software will map 18% gray to whatever your center f/stop is set to in the viewer settings (f/8 by default… change that to EV by following the instructions below).
    You can experiment with this by attaching an Exposure node to a Constant set to 0.18, setting your viewer read-out to Spotmeter, and adjusting the stops in the node up and down. You will see that a full stop up or down will give you the respective next value on the aperture scale (f8, f11, f16 etc.).
    One stop doubles or halves the amount or light that hits the filmback/ccd, so everything works in powers of 2.
    So starting with 0.18 in your constant, you will see that raising it by a stop will give you .36 as a floating point number (in linear space), while your f/stop will be f/11 and so on.

    If you set your center stop to 0 (see below) you will get a relative readout in EVs, where EV 0 again equals 18% constant gray.
    Note: make sure to set your Nuke read node to ‘raw data’

     

    In other words. Setting the center f-stop to 0 means that in a neutral plate, the middle gray in the macbeth chart will equal to exposure value 0. EV 0 corresponds to an exposure time of 1 sec and an aperture of f/1.0.

     

    To switch Foundry’s Nuke’s SpotMeter to return the EV of an image, click on the main viewport, and then press s, this opens the viewer’s properties. Now set the center f-stop to 0 in there. And the SpotMeter in the viewport will change from aperture and fstops to EV.

     

    If you are trying to gauge the EV from the pixel luminance in the image:
    – Setting the center f-stop to 0 means that in a neutral plate, the middle 18% gray will equal to exposure value 0.
    – So if EV 0 = 0.18 middle gray in nuke which equal to a pixel luminance of 0.18, doubling that value, doubles the EV.

    .18 pixel luminance = 0EV
    .36 pixel luminance = 1EV
    .72 pixel luminance = 2EV
    1.46 pixel luminance = 3EV
    ...
    

     

    This is a Geometric Progression function: xn = ar(n-1)

    The most basic example of this function is 1,2,4,8,16,32,… The sequence starts at 1 and doubles each time, so

    • a=1 (the first term)
    • r=2 (the “common ratio” between terms is a doubling)

    And we get:

    {a, ar, ar2, ar3, … }

    = {1, 1×2, 1×22, 1×23, … }

    = {1, 2, 4, 8, … }

    In this example the function translates to: n = 2(n-1)
    You can graph this curve through this expression: x = 2(y-1)  :

    You can go back and forth between the two values through a geometric progression function and a log function:

    (Note: in a spreadsheet this is: = POWER(2; cell# -1)  and  =LOG(cell#, 2)+1) )

    2(y-1) log2(x)+1
    x y
    1 1
    2 2
    4 3
    8 4
    16 5
    32 6
    64 7
    128 8
    256 9
    512 10
    1024 11
    2048 12
    4096 13

     

    Translating this into a geometric progression between an image pixel luminance and EV:

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    Read more: Photography basics: Exposure Value vs Photographic Exposure vs Il/Luminance vs Pixel luminance measurements
  • Photography basics: Color Temperature and White Balance

     

     

    Color Temperature of a light source describes the spectrum of light which is radiated from a theoretical “blackbody” (an ideal physical body that absorbs all radiation and incident light – neither reflecting it nor allowing it to pass through) with a given surface temperature.

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

     

    Or. Most simply it is a method of describing the color characteristics of light through a numerical value that corresponds to the color emitted by a light source, measured in degrees of Kelvin (K) on a scale from 1,000 to 10,000.

     

    More accurately. The color temperature of a light source is the temperature of an ideal backbody that radiates light of comparable hue to that of the light source.

    As such, the color temperature of a light source is a numerical measurement of its color appearance. It is based on the principle that any object will emit light if it is heated to a high enough temperature, and that the color of that light will shift in a predictable manner as the temperature is increased. The system is based on the color changes of a theoretical “blackbody radiator” as it is heated from a cold black to a white hot state.

     

    So, why do we measure the hue of the light as a “temperature”? This was started in the late 1800s, when the British physicist William Kelvin heated a block of carbon. It glowed in the heat, producing a range of different colors at different temperatures. The black cube first produced a dim red light, increasing to a brighter yellow as the temperature went up, and eventually produced a bright blue-white glow at the highest temperatures. In his honor, Color Temperatures are measured in degrees Kelvin, which are a variation on Centigrade degrees. Instead of starting at the temperature water freezes, the Kelvin scale starts at “absolute zero,” which is -273 Centigrade.

     

    More about black bodies here: https://www.pixelsham.com/2013/03/14/black-body-color

     

     

    Details in the post

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    Read more: Photography basics: Color Temperature and White Balance
  • 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. # The threshold_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:

    1. 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.
    2. 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, and 2 ** EV is used to convert the logarithmic EV to a linear intensity value.


    3. 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.

     

    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)
    , ,
    Read more: HDRI Median Cut plugin
  • Ethan Roffler interviews CG Supervisor Daniele Tosti

    Ethan Roffler
    I recently had the honor of interviewing this VFX genius and gained great insight into what it takes to work in the entertainment industry. Keep in mind, these questions are coming from an artist’s perspective but can be applied to any creative individual looking for some wisdom from a professional. So grab a drink, sit back, and enjoy this fun and insightful conversation.



    Ethan

    To start, I just wanted to say thank you so much for taking the time for this interview!

    Daniele
    My pleasure.
    When I started my career I struggled to find help. Even people in the industry at the time were not that helpful. Because of that, I decided very early on that I was going to do exactly the opposite. I spend most of my weekends talking or helping students. ;)

    Ethan
    That’s awesome! I have also come across the same struggle! Just a heads up, this will probably be the most informal interview you’ll ever have haha! Okay, so let’s start with a small introduction!

    Daniele
    Short introduction: I worked very hard and got lucky enough to work on great shows with great people. ;) Slightly longer version: I started working for a TV channel, very early, while I was learning about CG. Slowly made my way across the world, working along very great people and amazing shows. I learned that to be successful in this business, you have to really love what you do as much as respecting the people around you. What you do will improve to the final product; the way you work with people will make a difference in your life.

    Ethan
    How long have you been an artist?

    Daniele
    Loaded question. I believe I am still trying and craving to be one. After each production I finish I realize how much I still do not know. And how many things I would like to try. I guess in my CG Sup and generalist world, being an artist is about learning as much about the latest technologies and production cycles as I can, then putting that in practice. Having said that, I do consider myself a cinematographer first, as I have been doing that for about 25 years now.

    Ethan
    Words of true wisdom, the more I know the less I know:) How did you get your start in the industry?
    How did you break into such a competitive field?

    Daniele
    There were not many schools when I started. It was all about a few magazines, some books, and pushing software around trying to learn how to make pretty images. Opportunities opened because of that knowledge! The true break was learning to work hard to achieve a Suspension of Disbelief in my work that people would recognize as such. It’s not something everyone can do, but I was fortunate to not be scared of working hard, being a quick learner and having very good supervisors and colleagues to learn from.

    Ethan
    Which do you think is better, having a solid art degree or a strong portfolio?

    Daniele
    Very good question. A strong portfolio will get you a job now. A solid strong degree will likely get you a job for a longer period. Let me digress here; Working as an artist is not about being an artist, it’s about making money as an artist. Most people fail to make that difference and have either a poor career or lack the understanding to make a stable one. One should never mix art with working as an artist. You can do both only if you understand business and are fair to yourself.



    Ethan

    That’s probably the most helpful answer to that question I have ever heard.
    What’s some advice you can offer to someone just starting out who wants to break into the industry?

    Daniele
    Breaking in the industry is not just about knowing your art. It’s about knowing good business practices. Prepare a good demo reel based on the skill you are applying for; research all the places where you want to apply and why; send as many reels around; follow up each reel with a phone call. Business is all about right time, right place.

    Ethan
    A follow-up question to that is: Would you consider it a bad practice to send your demo reels out in mass quantity rather than focusing on a handful of companies to research and apply for?

    Daniele
    Depends how desperate you are… I would say research is a must. To improve your options, you need to know which company is working on what and what skills they are after. If you were selling vacuum cleaners you probably would not want to waste energy contacting shoemakers or cattle farmers.

    Ethan
    What do you think the biggest killer of creativity and productivity is for you?

    Daniele
    Money…If you were thinking as an artist. ;) If you were thinking about making money as an artist… then I would say “thinking that you work alone”.

    Ethan
    Best. Answer. Ever.
    What are ways you fight complacency and maintain fresh ideas, outlooks, and perspectives

    Daniele
    Two things: Challenge yourself to go outside your comfort zone. And think outside of the box.

    Ethan
    What are the ways/habits you have that challenge yourself to get out of your comfort zone and think outside the box?

    Daniele
    If you think you are a good character painter, pick up a camera and go take pictures of amazing landscapes. If you think you are good only at painting or sketching, learn how to code in python. If you cannot solve a problem, that being a project or a person, learn to ask for help or learn about looking at the problem from various perspectives. If you are introvert, learn to be extrovert. And vice versa. And so on…

    Ethan
    How do you avoid burnout?

    Daniele
    Oh… I wish I learned about this earlier. I think anyone that has a passion in something is at risk of burning out. Artists, more than many, because we see the world differently and our passion goes deep. You avoid burnouts by thinking that you are in a long term plan and that you have an obligation to pay or repay your talent by supporting and cherishing yourself and your family, not your paycheck. You do this by treating your art as a business and using business skills when dealing with your career and using artistic skills only when you are dealing with a project itself.

    Ethan
    Looking back, what was a big defining moment for you?

    Daniele
    Recognizing that people around you, those being colleagues, friends or family, come first.
    It changed my career overnight.

    Ethan
    Who are some of your personal heroes?

    Daniele
    Too many to list. Most recently… James Cameron; Joe Letteri; Lawrence Krauss; Richard Dawkins. Because they all mix science, art, and poetry in their own way.

    Ethan
    Last question:
    What’s your dream job? ;)

    Daniele
    Teaching artists to be better at being business people… as it will help us all improve our lives and the careers we took…

    Being a VFX artist is fundamentally based on mistrust.
    This because schedules, pipelines, technology, creative calls… all have a native and naive instability to them that causes everyone to grow a genuine but beneficial lack of trust in the status quo. This is a fine balance act to build into your character. The VFX motto: “Love everyone but trust no one” is born on that.

     

    , ,
    Read more: Ethan Roffler interviews CG Supervisor Daniele Tosti