Color Spaces: Explained from the Ground Up - Video Tech Explained

[@NicolasLunaFilms]

Well done. I've been a professional colorist for years... Now I teach color at a university in the film department... I was racking my brain for a good way to explain color spaces without overwhelming my students. This has helped exponentially.

[@dvoraklovelace2801]

Broooo you resume hundreds of hours of "masterclasses" in a single video. Thanks a lot!

[@gagan.dee.p]

All the concepts that you explain in your videos; I have never understood them with such clarity before. Your narration and explanation technique is elegant. I was able to follow you. Your content is devoid of unnecessary flashy video effects, shouting, and overacting. So no distractions or bs. Please don't change your style. Massive respect. You are awesome!

[@PriyaSingh-fj1mf]

Excellent explanation and succinct. Agree with the comments around saving HOURS of research/learning into a condensed video. Thanks so much for putting this together!

[@raulgalets]

this is the single video on the internet getting "what is color" almost perfectly correct. congratulations.

[@naratt]

Your content is such a hidden gem in KZbin ocean.

[@MitoDesign-o9u]

Just found this channel. Gonna binge tf out of it lol

[@Dhmey-Vip]

In fact, I was inside the editing application and found many options for color spaces and I changed the space and it said that it does not support that, so I wondered and searched and found your clip. I really thank you. I understood everything.

[@philippfrogel9355]

I am not even halfway through. This video is incredible!

[@coolguy137]

You are singlehandedly rendering it possible to understand comprehensibly subject matters that are core to an entire industry I intend to build a career in. THANK YOU ❤️

[@RobertFletcherOBE]

you'll soon find that virtually everyone misunderstands this subject and try to avoid it

[@king_of_baboons2032]

I don't work in this industry but I've spent years trying to figure out this topic. I did a lot of research and this video is the best among all of them. Fantastic job explaining everything with enough depth and reasoning!

[@ayacyte443]

I've been searching far and wide for an explanation- it finally makes more sense now. I don't think I've found such a simple yet comprehensive video.

[@numkim]

Thank you! I wasted a hour of my life trying to decypher the Wikipedia page and still don't understand it. This video explains everything immediately!

[@brightbytes5745]

I've been working on some videos in this area too, and man, you really nailed it! Nice job! Far and away the best content on YT on this topic

[@helloitsmehb]

I hereby declare you, King of Color Nerdism! Congrats and well done! Love your channel

[@franks.6547]

Very understandable and useful. Good job! To further understand, why there are always two opposing frequencies that produce the same colour impression, one could add to 6:37: With the assymmetric overlapping of the susceptibility curves and the approx. proportional response of each cone to the combined weighted intensity of all frequencies, Grassmann's Laws hold as follows: Any vector of three visible spectral frequencies (f1, f2, f3) maps linearly to (S, M, L) spanning a convex subset of a 3d vector space. Linear algebra then shows, that due to linear independence in 3d, even after projecting out intensity (luminence) to a 2d subspace, you can counteract any shift of one spectral frequency with a shift of the other frequency to get the same S:M:L impression. Then you tweak the horseshoe shape to make the lengths all the line segments, that meet in the same color impression, to reflect their mixing ratios. And this, too, is possible because of linearity and smoothness of the cone response.

[@eric-seastrand]

I learned a ton binging your whole channel a few months back. So excited to see another explainer from you. Great content!

[@coderdbd]

Amazing video, it deserves more views. I actually didn't know what color spaces were and now it is super clear. Thanks for the explanation!

[@Nugcon]

This clears up so much. Such a great video from such a small channel

[@Rey-j6r]

Goes to say people don't like it when it gets technical, but they miss out on good content.

[@utkarshkothimbire1484]

Thanks a lot, Camon for explaining all the concepts in a crisp manner. Very much appreciated. You have explained these complex concepts in very simple maner with the diagrams.

[@sushilskolia]

You deserve millions of views dude….. stay consistent 👍🏻

[@flexydex8754]

zero views*

[@earthoid]

I finally understand where the CIE 1931 color space got its shape from. Thanks!

[@valgustale]

absolutely loved it's one of the most helpful video i've watched in 2023 thanks for creating this mate

[@lorenzowood449]

Holy shit I appreciate you so much for this. Incredible video, this is what I wish all of KZbin would be more like

[@xtdycxtfuv9353]

Thank you. I will be returning to this video for many reviews until I firmly understand and always remember.

[@largemagellaniccloud8153]

Thank you very much, Camon, for your excellent videos. You are a very cogent thinker and presenter.

[@ocean457]

This kid is a riot! Bravo!

[@TeddyCavachon]

The human retina has two types of light sensing cells, rod and cones. The rods are only sensitive to a narrow range of wavelengths in the green region but significantly are nearly 3000x more sensitive to light intensity than the cones which sense red, green and blue, respectively. The rods cover the entire retina, but the cones are mostly concentrated around the optic nerve. The greater sensitivity of the rods and their location explain why at light we can see movement at the periphery of our vision better than in the center and why when our eyes fixate on objects we get “tunnel vision” which is the brain’s way of mentally tuning out the much stronger signal from the rods. The rod / cone physiology explains why the CIE*xyz graph used to represent color space is much larger in the green region and why staring at bright green colors becomes fatiguing. Red lighting is used at night on control panels because the rods don’t detect it making it easier for them to detect any objects in other areas viewed.

[@EdiWalger]

rods are sensitive of a broad range of wavelengths. The peak is near to cyan, and excludes reds, but the range is broad. Sensitivity or rods are not derived from a single cell, since a lot of rods are combined in a single ganglion. That means a collection of small sensitivities added together, since the small size of every rod and the huge population of them. Cones are concentrated in the fovea (not around the eccentricity of the optic nerve) and rods do not cover the fovea at all. Because of that you cannot see a star at night with the center of your vision. Movement definition of rods are related with the speed of the visual cycle of them, not from sensibility.

[@TeddyCavachon]

@@EdiWalger Thanks for the multi-spectral enlightenment 👍❤️

[@PrestonRahim]

Great video. Really helps grasp the idea of a very mathematically implemented concept that is derived from a subjective experience. I would only mention that I believe the equation at 7:18 should swap the position of your transformation matrix and your LMS vector in order to make it a valid operation.

[@robertulrich3964]

Correction: RGB is a non-perceptual color model, not a colorspace. HSL is a perceptual color model that takes into account human vision. Rec. 709 is a colorspace that defines primaries in locus points to derive relative coordinates to CIE 1935. You can convert to other colorspaces using relative or absolute colormetric intent with prioritizing white balance against saturation. (so even the transform conversion itself can be perceptual). Additionally the camera's RGB sensor array only exists in the world of a standard exposure (usually 18% grey) so it's data is not truly 3D in nature since camera's sensors give non-linear response to light. In essence, every camera has a custom color model. This is why it's hard to match cameras that have varying scene referred color over an exposure range. And adds to the reason why lookup tables do not work as well as anticipated.

[@EdiWalger]

HSL is "perceptual"? No, is just a projection model from an RGB model by using a very simple transform. Not a colorspace, just a different color "model". Camera sensor are possible because the photoelectric effect, which is "linear" in transduction by nature, that means all sensors are linear in response, but each can use a different encoding at the time of saving data only. Cameras has a custom "colorspace", not color model.

[@robertulrich3964]

@@EdiWalger The HSL representation models the way different paints mix together to create colour in the real world, with the lightness dimension resembling the varying amounts of black or white paint in the mixture (e.g. to create "light red", a red pigment can be mixed with white paint; this white paint corresponds to a high "lightness" value in the HSL representation). Different cameras can have the same colorspace but different spectral response in the sensor. The spectral response over overexposure is what causes irregularities in matching cameras and that mapping process is non-linear despite transduction.

[@EdiWalger]

@@robertulrich3964 the QE of every sensor can be different by wavelength, and the colorspace is the result of the camera calibration that you need to reproduce real colors. Every wavelength stills with a linear (proportional to radiometric intensity) response, but changes for every wavelength. L (lightness) is an abstraction that must be defined mathematically, and never match with any "perceptual" concept, specially in the HSL projection: you can define a color with hue/sat but no lightness, which is impossible to realize. Because of that HSL is "derivative" from RGB that defines the real color mixing, and not a colorspace made from abstract attributes. Just an indirect manipulation for the RGB model which results in a non-perceptual match: color cannot be fully represented by euclidean dimensions.

[@Rey-j6r]

Thanks for your useful comment.

[@devlin1991]

Great video, I'm on the hunt for good, concise, videos on this topic to share with some work colleagues. This knowledge is not taught in most software courses so is a bit of a black box abyss for most software engineers. I keep running into "two wrongs make a right" scenarios that appear out of nowhere when one colospace bug is fixed. Thank you for making this content. If there's not another video from you that I've not seen yet, I hope you cover gamma transfer functions as well, PQ, slog, sRGB, etc. Because that's arguably even more confusing than the colorspaces, especially when sRGB color primaries (Rec.709) and sRGB gamma transform are often used interchangeably online.

[@99SBX]

This is my new favorite channel!

[@braunventures]

brilliant, thanks for helping me build knowledge on a strong base

[@m14b]

Awesome video! Thanks for the explanation much more detailed!

[@mattkarikomi5947]

This is concise and very clear, nice!

[@colinwood1337]

Wow! I’ve been struggling to understand colour spaces and now I do! Great video

[@crew_the3rd]

Glad to see some objective science being applied to color theory. Note there is a huge difference between light color theory and pigment color theory. To start 6 Primary 3 Light >>> Red Green Blue 3 Pigment >>> Magenta Yellow Cyan Pigment Derived Red=Magenta×3+Yellow Green=Yellow+Cyan Blue=Cyan×3+Magenta 6 Secondary Pigment 3 Common >>> Violet=Cyan+Magenta Rose=Magenta+Red Orange=Red+Yellow >>> 3 Obscure >>> Chartreuse=Yellow+Green Aquamarine=Green+Cyan Cerulean=Cyan+Blue Other Purple = Blue+Red >>> >>> >>> >>> Rant ROY G BIV is a mistake and there are several issues. 01 Cyan is mislabeled as baby blue and Magenta gets left out most of the time 02 Indigo is not necessary, it's not even a secondary color. It's a dark dark violet that is more on the blue side. 03 Purple would make more sense than Indego, and fyi purple is not true violet. Purple = Blue + Red, Violet = Cyan + Magenta 04 Blue and Violet should have been separated correctly but instead indigo gets used 05 In light, Violet exists in two different ways, it has its own distinguishable frequency and wavelength, but it can also be created by a mixture of blue and red wavelengths (the human eye will except both versions and they are not distinguishable to us). This duality makes it a bit confusing in some situations. Note there is a huge difference between light color theory and pigment color theory. 06 Purple is a type of violet. Slightly darker with more red. Purple = Blue + Red, Violet = Cyan + Magenta 07 Indigo is a dark dark violet, closer to the blue side. 08 Violet is a wider spectrum (than the other colors) because it can be a mixture of blue and red light at different ratios. 09 Magenta has a similar issue as violet but magenta actually does not exist as a single wavelength/frequency in light. Magenta is the 1 to 1 ratio (1:1) of red and blue Light. Magenta does not exist on the rainbow but we can clearly see it's place in color theory. 10 Indigo and Purple are not necessary when considering primary and secondary colors (6 primary 6 secondary [derived]), they just fall under violet. 11 M ROY G CBV M, I distinguish 8 unique colors that we seem ti care about most, the 6 primary plus orange plus violet. 12 Aquamarine (green-cyan) is on the same level as orange and violet but in our culture we don't value it as unique. 13 If you only consider the rainbow then you would not get Magenta and the 8 would become 7 which is what you see in the rainbow ROY G CBV.

[@tompainter7167]

Thanks the CIE and XYZ stuff is HARD for artists but this makes it easier thank you

[@devendrapisda3528]

this 16 min video took me one and half hour to complete. Never been into this so it took me time to really understand what you are teaching. My mind is blown brother. This is what I needed since don't know how many days.

[@DennisForbes]

Absolutely fantastic video.

[@AbrEvig]

Excellent, simply excellent!!!

[@renesarlo6211]

great work thanks

[@guymross]

Wow best color theory video to date.

[@gregoryflinn3577]

What your previous video does still contribute to this topic is the colormetric transformation needed between color spaces to ensure that what the camera saw is what you see on the monitor. Whether that transformation is absolute or relative is e.g. part of the answer to a question below on why someone still sees ‘all’ the colors of CIE diagram.

[@AMRARDvermebrungruppe]

One of the crazy things I learned today is that the medium-wave cone's sensitivity peak is 520 nm. The color of 520 nanometer light is perceived 'in my culture' (which culture is one with one word, blue, for what are distinguished as gorm and glas in Celtic cultures) as within the category of BLUE rather than as GREEN. This was so confusing to me for a long time, but you can see where our cultural expectations start to mask reality because whenever we make an illustration of the three cone cells, when we call them "red, green, and blue" we automatically imagine/illustrate that "green" as like the color of grass or foliage. But in reality that "primary green' color is actually somewhat to the red-end of the medium cone response range. The "green" cone actually responds primarily to the color of shallow seas or waves breaking. It all makes more sense when you see the CIE 1931 space because almost half of the entire diagram is basically perceived as shades of aqua or teal, with four of the 'rainbow colors': green, yellow, orange, red, all compressed into a very small range of wavelengths which our eyes are particularly sensitive to discerning.

[@vrmeup]

Thanks for a great video 😃. It was educational, interesting and has cleared up many of the misunderstandings I had about color in my ThreeJS computer graphics application. You did a great job of explaining a complex topic!

[@tyt03538]

Thank you so much. This is the best colour space explained video!!!

[@Urtana]

Best of the best. Thank you .

[@RobertNuwagaba-n8z]

Thank yiou Camon, this is insightful information

[@torjusaanderaa3749]

Daaaaamn thats an impressive explaination, well done! :D

[@jleocarmo]

Excellent video, really helpful and insightful. Thank you!

[@dpi3]

excellent!

[@sunviewer7]

Amazing

[@EdiWalger]

11:53 The CIE1931 is not an "absolute colorspace", since Y means a percent of a "luminosity scene" estimated from a luminosity function (CIE1924). A real absolute colorspace uses cd/m2 for luminance, like ICtCp. But 1931 is an "absolute gamut", in terms of chromacity inside of an unknown dynamic range.

[@austinbly2141]

Amazing summary - thank you very much!

[@cthaneshh]

How do I even thank you for such valuable content!

[@nobody-bt7mu]

That video was really helpful for me! I'm glad you decided to create a better one! On another note, would you be able to make a video explaining monitor calibration types? Cheers!

[@terrytang5367]

This dude is knowledgeable!

[@MaximoJoshua]

This video is amazing, just masterful. I hope you make a part 3 going over gamut mapping (moving from a larger color space to a smaller one) and things like the Abney Effect, etc. Do you have a patreon or something? These are some of the best videos on the internet when it comes to talking about color and digital video.

[@_burd]

It's kinda cool that metametism isn't actually a phenomena of physical light, but a limitation of our 'three cone' based measurement tools :) While it makes sense that we use RGB sensors to account for this, I kinda wonder how useful it would be to use a different architecture to capture the light spectrum so the data can actually differentiate from a spectral 'yellow' yellow and a yellow created by red/green pollution. Things light scene light pollution could be targeted directly in colour finishing without effecting something which is actually supposed to be that colour.

[@g.t.m.thurlings4882]

Chapeaux, very good. Good video well done.

[@dennishancock]

Keep up the good work!

[@urbanskargren5566]

Very clearly explained, thank you

[@AnonyMous-rr4gf]

Thank you for making this.

[@cnb3388]

Great explanation.

[@karasu9]

extremely good video

[@Pheonixrocks]

Man this is uni level quality of education

[@milkandhenny]

This is a fantastic video.

[@ayeshaarfaat]

If my screen is sRGB and it cannot show colors outside the triangle on CIE diagram then how can my screen show the full diagram? Shouldn't I see just a triangle?

[@VideoTechExplained]

The colors which are outside your display's gamut are shown as being the most saturated possible color of that hue. So the part of the diagram which corresponds to your display is accurate but the parts outside of it are not. The colors on the diagram are only used for visualization purposes

[@pedromj9689]

Congrats and thank you for the explication. Really well done

[@design_ref4215]

This explaination is amazing.

[@nikkilin4396]

Best explanation!

[@luxyAAA]

This is great!

[@ladikable]

Very good presentation! Keep it up

[@pearlgardenshop]

Thank you

[@oxkaioxo]

Very nice video. Instant subscribe.

[@CptCurk]

great content. I need a summary of that topic to remember school ^^' And your video is accurate and right ! :)

[@rafograph]

Great explanation

[@vladalex9556]

Linus Tech Tips vibes, good video I like

[@soumyadeep-mondal]

Thank you so much for it. And, please add CIELAB and HCT also brother.

[@VideoTechExplained]

Those were in earlier drafts of this video, but I ended up cutting them because this video was pretty dense already. I'll most likely cover them sometime soon!

[@soumyadeep-mondal]

@@VideoTechExplained Lots of love from this side man. I really appreciate your hard work!

[@Bradum]

This video is so good!

[@isabelsun5299]

brilliant

[@Вондери]

THANK YOU MAN...

[@design_ref4215]

Thanks

[@benloud8740]

Great video

[@tailaihaha]

thank u sir!! Thx for educational info!!

[@vanyakapetanovic4018]

Hats off man.

[@nando603]

What a great video!!!!!!!!!!!!!!!

[@soulcstudios]

I spent 3 hours on Wikipedia and a bit of KZbin trying to understand why if the 3 lights making up a pixel correspond to the 3 cones in the eye, my monitor can't reproduce the entirety of the visible spectrum. The CIE 1931 (I read that wikipedia page) and THEN the R G B color space put it together. I thought this was a really simple question when I started but wow, nope.

[@ShishaWG]

Anybody know the name of the music piece at 0.40?

[@VideoTechExplained]

"In the hall of the mountain king"

[@isaac10231]

Insane video

[@jason-ps6mf]

7:17 the column matrix {L M S} should be at the right of the 3 * 3 matrix

[@Retro28YT]

Great video! Very informative :) it's a shame it only has 1400 views.

[@sobhhi]

Bro knows math I love it

[@esbo69]

Great video! what software did you use to make the cieLab visualization? Thanks!

[@celestinbueche]

youtube at its best!

[@SATORvii]

Great video dude! I learned a lot! You might need to find someone to iron your shirt though lol.

[@emotional-robot-dynamics]

Great explanation of a very complicated subject 🌟 love the graphics (!) really helpful with the visualisation process... 🌟 would you consider making a video focussing on the 'OKLAB' colour model >> I think that would be very interesting >> keep up the good work 👌💯👀🎯🖼😎🌠

[@mustafakamal8608]

This is great content.❤❤ My questions are how do you identify color transformation / color space made by LUT ? What reference and tool should I learn if i Interested in LUT / look development? I'm learning color grading using davinci and intersted in look development and film LUT.

[@TriPham-j3b]

Color can be view as acceleration of time space like acceleration of acceleration or torsion( vector product of heat and sound and sngle between the two vectors