How are Images Compressed? [46MB ↘↘ 4.07MB] JPEG In Depth
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- Опубліковано 14 тра 2024
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You've probably saved 1000s of JPEG images, but do you know what exactly JPEG does? Our smartphones and cameras save images in JPEG format, furthermore, the majority of images you see on the internet are saved using JPEG compression. This format is everywhere, but do you know exactly how it works? Well in this video we're going to explore the JPEG compression format. This is a rather complicated video, so it may take watching it a few times through to understand it all.
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Script, Modeling, Animation: Teddy Tablante
Twitter: @teddytablante
Voice Over- Phil Lee
Nature Photography- Tobias Karlsson
Table of Contents:
00:00 - Intro into JPEG
01:24 - What does JPEG do?
02:35 - What are the Steps of JPEG?
04:06 - Color Space Conversion
06:06 - Discrete Cosine Transform
09:32 - Quantization
11:02- Run Length and Huffman Encoding
12:04 - H.264 Video Compression
13:25 - Rebuilding an Image
15:01 - Notes and Caveats on JPEG
17:06 - Sponsored by Brilliant
18:20 - Outro
Key Branches from this video are: How does a Camera Work? How do SSDs Work?
Erratum:
Tulips are not the same as Lillies.
Animation built using Blender 3.0.0 www.blender.org/
Post with Adobe Premiere Pro
References:
A Trip Through the Graphics Pipeline 2011: Index
fgiesen.wordpress.com/2011/07...
DCT (Discrete Cosine Transform)
asecuritysite.com/comms/dct2
H.264 is Magic
sidbala.com/h-264-is-magic/
How JPEG Works
cgjennings.ca/articles/jpeg-c...
Jack, Keith. Video Demystified. Fifth Edition. Elsevier 2007.
JPEG 101 - How does JPEG Work?
arjunsreedharan.org/post/1460...
JPEG: Image Compression Algorithm
pi.math.cornell.edu/~web6140/T...
What is H.264?
www.streamingmedia.com/Articl...
Wikipedia contributors. "Chroma Subsampling", "Chrominance", "Chroma Subsampling", "Discrete Cosine Transform", , "JPEG" , "
Wikipedia, The Free Encyclopedia. Wikipedia, The Free Encyclopedia, Visited December, 2021
Music Credits
Kindred
#JPEG #Camera #Picture
It never ceases to amaze me how much computation goes into things we take for granted and how inconceivably fast it happens over and over again...
Still images are fairly easy, the compression is relatively simple. Video is a lot harder to do quickly in software, especially compression, which is much slower. Computers, and especially smartphones have ASICs (Application Specific Integrated Circuit), to do it much more efficiently. Instead of general purpose CPU doing it, a circuit that is hardwired to do exactly one thing is used, offering massive efficiency gains, which are absolutely critical for use in low power devices. Software is more flexible, and tends to be able to get higher compression, or better quality for the same compression, at the expense of processing time and power usage.
What amazes me the most to this day is how we can have phonecalls moving at high speeds without an issue. It's like, how fast does it really happens??
@@rockraphlegal that's where processing power matter, that's why some chips are better in image Manipulation wrt to other
No need to be amazed. Just take a simple can of soda, the time and efforts it took takes years to come out with today's design.
@@weizhen77 that too amazes me :P
This channel is researching and (perfectly) presenting exactly what you think in your spare time
You are extremely right!
Ohhhh so this is where our google data goes!
@@sifanikalsa9790 88
@@sifanikalsa9790 damn this is hot
ua-cam.com/video/fx6jtJrvJzU/v-deo.html
As somebody who has worked on JPEG implementations, I am still amazed by how perfect they got it on the first try. JPEG has been around for ages, and is still so good; only recently have meaningful replacements emerged, and JPEG still has some benefits over these.
What is this replacement?
@@eduardmart1237 webp maybe ?
@@allkillhon5209 avif is good too, although not widely supported yet. webp is much better than jpeg, don't really know why it hasn't been adopted widely yet
@@zxbryc JXL is definitely very interesting, although I don't know too much about it. I just think with rising performance in almost everything, and hardware decoders for AV1 & AVIF in new phones it might be a viable option in the future, for fast image loading on bad mobile connections for example
webp is trash though.... not much advantage vs jpeg and lots of compability issues. Instances when a site uses webp for own images but doesn't allow webp image upload is annoying. Windows can't open it out of the box, PS needs a plugin.... And that despite the format being out for 12 years
10% better compression might have been nice 10-15 years ago, today people have 100mb/s in their phones and gigabit via fiber, whether an image takes 1mb or 1.1mb doesn't make any difference.
Up until now, I just thought JPEG lumps some similar colours together to save on file size. This was literally eye-opening. What an algorhythm!
That is like 5% of it. There is alogoritmoc coding, and other things.
You were probably confusing it with the GIF format. It stores images with a limited palette so the numbers of colours in each imge is reduced. But unlike JPEG it allows transparency and animation, so despite the greater file size it was popular on the early web.
Tbh, I didn’t even know JPEGs were compressed.
@@plashplash-fg6hd Moreover, JPEG is not just the image format, it is a compression algorithm. For example, one can use it in TIFF images. Damn, what obsolete trash! And it was obsolete trash already at the time of this publication.
@@Micro-Moo Never knew that.
You cover topics that I've always wanted to know and in the right amount of detail.🥰
Not compressed too much ;)
true that
The perfect reason to cancel all school loans. If youtube is going to tell everyone everything for free. You do know one day there won't be a pandemic right or a bunch of chaos coming from trump and his followers right? One day. You're just going to be competing with everyone who knows the same crap as you.
Exactly so relatable for me
YES SIR
as someone whos on youtube a lot, these still manage to be some of the best videos. The research, editing, the pace of the lesson. Thank you guys for the hard work
An absolute masterpiece of explanation. I've tried to understand how DCT works in JPEG before, and never understood the dry maths-only explanation. This video changed that and the image tables explained it perfectly. Thanks for filling in a gap that's been in my head for many years!
Great explanation on JPEG. I knew it compressed in blocks, and I vaguely knew it averaged color, but seeing this level of detail is amazing. Well done!
There's just nothing like these videos, really. I'm blown away every time. The voice-over and writing are just so far beyond anything else out there. I wish all information could be presented in this calm, clear, and concise manner than also somehow manages to never dumb it down.
you mean his compression algorithm is pretty good?
dumb @@YszapHun
I have a degree in computer science and I'm still amazed how good your channel is! Always wondered how JPEG compression worked. You have illustrated it in super simple terms and visualizations have as always been awesome! Happy to see more content like that, maybe more details on H.264.
lol I dont have a degree, but I already knew this.
@@kangarht good for you
@@m.moonsie you look happy and healthy, not me, if you ever cared to aaask
Having a degree means nothing though. It doesn't guarantee that you know even a tenth of what's there in your own field.
@@pedor5965 lol
It's truly impressive how you managed to explain these complex processes in less than 20 minutes! The clarity and conciseness of your explanations made understanding these concepts much easier. Thank you!
really love the little details, the secondary animations in each text header for each step in compression being unique to that compression technique itself.
praise your mograph artist/animator/editor!
Great Video, just a little feedback on chroma subsampling: The reason why the human eye can perceive more luminance resolution than chroma isn't because of the number of rods vs cones. The rods are actually inactive in all but the darkest lit environments, and their density in the fovea i.e. the center of the visual field on the retina is actually rather low. So the RGB cone cells are solely responsible for tristimulus color vision.
The actual reason for the color resolution difference is because there is some amount of cell level processing happening in the eye before the signal reaches the visual nerve. This is very much analogous to the Lightness chroma separation done in digital images. Also, there is some correlation between spatial resolution of each of the red, green and blue cones in terms of the lightness but little correlation between them in terms of the color. Those effects together cause the lower chroma resolution of the human visual system.
Thanks for your input
No
@@blackpepper2610 What are you saying?
"..actually inactive in all but the darkest lit environments, and their density in the fovea i.e. the center of the visual field on the retina is actually rather low." So that's why when I am in dark I see some very dimly lit stuff more clearly when not looking directly at it, but the moment I move my vision towards it, it disappears?
What's the likelyhood of having hexastimulus color vision...like prawns...but in humans. Is it possible to design a baby capable of this?
Another factor that compression works so well is that your brain all the time fills in the «gaps» in information. Especially when watching video. Our eyes is actually worse than you think. The brain does a huge amount of work filling in various gaps in information. For example each of our eyes has a blind spot. We usually do not see it since the brain erases it and fills in the missing information
We have built in image upscaler.
@@prateekpanwar646 with great edge detection neuron layer 😁
It also combines 2 separate images with slightly different angles into 1 👀
@@markjacobs1086 like 3d glasses but free
Is there anybody in this world I can trust?
I never thought that there was so much computing behind each image. I am truly humbled by your work team. Thanks!
The is the best and clearest explanation of JPEG compression that I have seen anywhere - great job!
Since the very 1st video I watched, this channel is one of a very few that I clicked the bell button without even thinking twice, each subject is presented with great clarity, beautifully illustrated and great narration as well. well planned, edited and organized by key topics.
This is... AMAZING. It's probably almost impossible to explain this even just marginally better. The amount of well-considered effort you go through to make things more clear is extremely impressive. Subbed!
Wow how have I not discovered this channel before. The production values are off the charts !!
usualy videos like this claim to explain something but they just talk about it and dont explain anything .... but THIS video does actualy explain the techniques behind it i love it ... those vids are rare and hard to find .thank you for all the work you put into this
Your videos are SPECTACULAR! It's obvious that you put a lot of work into them, and it shows. You seem to intuitively know how to achieve the perfect balance of technical detail and higher-level concepts to enable the viewer to develop a solid overall understanding of the subject matter. THANK YOU!
18 minutes to teach us what our smartphones does in miliseconds. Awesome!
You sould try CPU! post video!
Been through multiple articles and videos about JPEG compression, I must say this is one of the best!
Underrated Chanel, this channel has everything you would like to know with details, good content. Keep going 👍🏻
It is incredible how complex things that we take for granted on a daily basis can be
And this is the reason why religions are accepted and exists in the first place.
Because it is more convenient for a LOT of people to think about complex topics as 'magic' and 'just works'...
@@temp50 I don’t think any religion says that
@@nickwilson3499 They don't say anything meaningful anyway.
Every time I remain surprised by the amount of quality and work behind your videos, wow
Came across your channel this week. Must say that your explanations are exceptional in the sense that they convey technical details very clearly and also very quickly grab the attention of the viewer. Exceptional i tell you. Keep it up. You should he used as the benchmark for teachers and lecturers all around the world.
This channel is a treasure to preserve, it covers modern and intriguing topics that are both mesmerizing and reaching for curiosity in technological mindsets, I love it.
I love this channel! Super informative, great presentation and one with the best content in UA-cam. Thanks for making those videos and please keep up the good work!
WOW this is so detailed! So much more information than most videos will tell you. Down to a fundamental level, not just “it works better”. Thanks! I’ve been interested in how video/pictures are compressed
I watched so many of your videos but this jpeg algorithm for image compression is so complicated that no one can understand in first time but you are amazing
I am really amazed by the research and hard work you put into making this video. Subscribed !!
Even though I always knew the basic idea behind compression this video finally gave me some real understanding - well done for a very complex subject
Amazing video as always!! The detail of explanation is precise and technically correct. I think that, once understood how JPEG works, MPEG should be not very difficult to understand.
If you plan on doing videos about electric engineering topics, I'd love to see a video about OFDM access, and how it is used in 4G for letting hundreds of users connect at the same time at an e-Node B. Can't wait for the next video though!
I'm mechanical engineer.
I've learn fourier transform since Bachler degree , one of the most unintuitive subject in my opinion...
And this video, i think this is one of the most intuitive way to explain "DCT" discrete cosine transform.
Great work !
Fascinating stuff. I still remember when JPEGs first came out and waiting for my DOS machine to encode and decode them. It took some time back then and not so instant as it is today. I think the two file formats that made the biggest impact in sizes that I recall in my life were JPEGs and MP3s.
I never thought I can understand the basic of JPEG algorithm in less than 20 minutes.
Brilliant video!
I am amazed by the 3D transitions between different 2D text/diagram sections. This form of presenting learning feels closer to learning in VR. I wonder if one day this channel will create VR episodes which we can move around in. Great delivery of a new way of learning!
Digital imagery takes up a great deal of my time for what I do, and I know from practice what file formats and compression do, but I never really looked into how they work. Thank you!
As someone who has studied image and video compression at university, I can say this is a GREAT video and it's spot on. It explains the basics in just the right amount of detail to get a general understanding. Would have helped me a lot in the beginning.
Any book to recommend?
One of the best educational channels on UA-cam!
Fantastic video, as an electronics engineer its pretty amazing to see topics such as frequency response being used everyday in our lifes
Incredibly well explained and visualized. Thank you so much!
I like the slower pace because it helps me to understand/think through what you say (but I'm no native speaker).
Lol I just got shown this random channel with great quality narration, animation and explanation. Subscribed
The amount of efforts you are putting in your video is amazing
I was wondering why I was subscribed to this channel then after a minute in I remembered how well the bluetooth explanation you(your team) have made. Thanks, the explanation is topnotch (imo of course) but there were few graphical error and some color selection could have been better.
This is incredible. Easy like, easy subscribe. Time to go through your entire video history!
Hey really thanks man! I was tod to take a seminar for mpeg conversion even though I saw many articles in Wikipedia and watched many videos I can't able to understand but your video about jpeg conversion have given me enough knowledge to explain the concept of mpeg conversion
Great video, I basically knew everything as my research is in video compression, I love the fact that he said video compression is extremely complex while giving an example of H.264, which is quite old now, it's still the most used for sure, but the newest codec VVC (versatile video coding) is times more complex than even HEVC which is newer than H.264, my work is in VVC, believe me it's a nightmare, don't take the videos you watch on the internet for granted ;)
I am curious to learn about the potential of the new codecs to be developed. I tried some google search but it looks difficult to find understandable source of information. Do you have any recommendations to start with ?
Used to be I followed these things out of curiosity - where does one do that now? 🤔
Interesting, I hadn't heard about VVC until now. As the successor to HEVC, which competes mostly with VP9, is VVC seen as a competitor to AV1 (since AV1 is the successor to VP9)?
ua-cam.com/video/fx6jtJrvJzU/v-deo.html
@@barbecue1617 ua-cam.com/video/dQw4w9WgXcQ/v-deo.html
and they say perfection isn't achievable.
this is an honestly amazing video and now I'm going to write a jpg parser and decompressor just for fun because you made it.
I also do embedded development, and a microprocessor I was working with had hardware jpg decoding - yet I never really thought it could be something this simple because when I googled it all these complicated terms came up. I didn't stop to think that hardware implementation are usually only feasible with simple algorithms. but now I'll know better in the future
I've also been aching to implement h.264 decoding on an fpga for direct network playback (so I don't need a nasty closed source firmware raspberry pi to do it), so I can't wait for that video too! I've been trying to read up on the subject but good resources are essentially non-existent. this video alone already helped me a lot in that regard, so even if you only release the h264 one in a few months and I'm done with at least a simple software implementation by then - I'll still watch it just because your videos are great, and much of that will still be owed to this very video right here.
thank you!!!
" I didn't stop to think that hardware implementation are usually only feasible with simple algorithms."
Any algorithm can be implemented in hardware (chip/transistor level), simple or complex. Logic gate structures can form turing complete computation, just the same as the general processors that use them. This also can drastically speedup the computation due to less clock cycles for the same task (no overhead for instruction sets and less data shuffling).
Still had my window up and figured I'd clarify another thing:
"yet I never really thought it could be something this simple because when I googled it all these complicated terms came up."
The actual implementation is much more complex than this video lets on. It's an excellent video for a general overview, but he skips through pretty much all of the math and even gets a few things wrong (like misusing the term 'vector' when discussing issues with Jpeg compressing a raster... but vector is entirely orthogonal to raster). The actual implementation deals with the math of fourier series and fourier transform, whereby an arbitrary signal can be represented by a summed series of cosine (and sine for complex) signals with a specific amplitude coefficient and phase. If you write a Jpeg parser, it would likely be beneficial to understand this math, though you can probably implement the algorithm without understanding it, just by running through the format documentation.
As for the h.264, I'd be surprised if there isn't already an FPGA implementation of that floating around out there. However, it is licensed, so maybe they're protective of direct implementations just floating around, not sure.
I was expecting a normal UA-cam video that rushes through everything and makes no sense, but wow was I wrong, these videos are easily understandable yet also really in depth.
I just came here to say I perfectly understood how JPEG works from thumbnail . I love you branch education so high class
I'm a photographer and I always wanted to know this. I didn't understand anything. But great video. One day I will watch it again. Hopefully I will, then, understand it.
Phenomenally well explained as usual!
I've just seen the video and realized that you released the video just two days after I submitted my bachelor thesis about forensic jpeg algorithms :D Would have been great to have these visualizations back then but nonetheless great and simple explanation with really good animations!
உங்கள் மதிப்புமிக்க அறிவைப் பகிர்ந்தமைக்கு நன்றி.
Thank you for sharing your valuable knowledge.
my brain hurts
Great video! JPEG is actually significantly simpler than I thought, thanks to your explanation. Would be great to have a video outlook into machine-learning based methods and the future of compression.
I'm so glad that because of some great people out there, this channel exists.👏👏
I really appreciate it. This tutorial video was perfect. So far I have watched more than 10 videos to understand the JPG process and your video was more beneficial than those videos.
Good Job man!
Back in the early 1990's I designed and worked on 'Slowscan' security systems over dialup modems.
This was in the early days before the JPEG standard was published. We used our own Discrete Cosine Transform (DCT) based image compression, empirically tuned for the product's target usage. We actually used a hardware circuit to detect when an 8x8 block had changed enough to mark it as 'to be updated'. Due to the low processor computing power available at the time, the DCT was performed by an INMOS DCT/IDCT transform chip. The compression stage was left to the modem's built-in algorithm, such as V42bis.
Awesome history lesson, thank you for writing this.
That’s amazing… amazes me that humans created all this.
Nice, love details and simplicity in explanation of how it work.
Small tip for far future video idea: accelerometers and gyro/magnetic sensors.... I always loved to read on how they managed to make those sensors.
I think they have like 2 pieces of metal that change resistance based off the orientation. not sure tho I just remember reading that somewhere
@@sierra991 It actually use MEMS in scale like one or two µm that is insane(as most of stuff that is in nano scale) but in that small scale it need to be super accurate and still robust.
Its just mind blowing that we managed to create few atom size transistors for eg SSD or OLED screens but mechanical components is just another level as its need to move in very specific way and best part is that MEMS technology is "low-cost"... its easier to make than grow damn tomato plant -_-
Wow I'm so happy and excited for this video... videos that give deep understanding like this are rare.
Quality oozes out of these videos. Thank you. Amazing work!
Good thing to emphasize about the dct is that it's also reversible -- you get the same amount of information out as you put in, just arranged in a different way. (I explain this to myself by noticing that the frequency samples are all linearly independent -- none of them can be added to each other to make a third, no redundancy -- so you've switched from one 8x8 block of data to another 8x8 block of data.) This sort of thing (fourier transforms and cousins) are super important for signal processing
Also, you should take a super deep-dive into how Laserdisc works. I get the basics of it, but still would be nice to dig into the actual nuts and bolts of the format. :D
Thank you so much for this video, my professor wasn't really explain DCT and Qunatization to me, but the visuals used in your video helped so much, and I feel like I finally understand it!
Beautiful video! Great transitions, intuitive and relaxing
Those signal processing algorithms behind the scenes are amazing. Especially the transforms that have been taught in the colleagues should not be rely on the mathematical calculations, instead there should be more visual explanations like this. Amazing video by the way!
the JPG at the beginning has richer contrast and deeper colors
Thank you! I was wondering if anyone else noticed this. It was so immediately apparent
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to me, the compressed example looks more colorful and with more contrast. If anything, the uncompressed image has slightly better dynamic range in the shadows
Câmeras when shoot jpg aply on algorithm saturation sharpening etc... Things that you would do to a raw file on a editing software
no xD
I haven't had my mind blown like this in quite a while.
Partially also because of the fantastic presentation.
incredible, I would never have thought that there is so much complexity behind a jpeg image
JPEG stands for “Joint Photographic Experts Group”. It's a standard image format for containing lossy and compressed image data.
We needed an open standard, the CompuServe GIF Image Format was dominant, PNG for professional use and for reviewing only JPG
@@lucasrem1870PNG and JPG are two very different kinds of compression, and as such, good for very different things.
PNG is a lossless compression which deals the best with "blocky" images, i.e. where there are a bunch of consecutive pixels with the exact same color adjacent to each other. This is, for example, includes (rendered) text or (vector, engineerinng) drawing on solid color background, or similar ideas. These can be compressed to very small sizes with PNG without any artifacts, while the JPG-compressed counterpart will be worse in quality and most of the cases even bigger in file size (than the PNG version).
However, compressing natural images where there are a lot of color gradients and edges, while it is possible with PNG, it is rather "encapsulation" and not really compression, as the file size will not be meaningfully smaller in most of the cases. This is the territory where JPG is better, provided that you are okay with it's lossy nature.
Compression is amazing technology. I remember when the Surge 1 was been released. It was only 6gigs or so but the game was really large with many enemy types, a lot of music and many weapons and amour. I was wrecking my brain trying to figure out how in the world could they fit such a large game into such a small file size. I am still at a loss ist at how they did it. Even with this upload, it still feels like magic haha
This video gives me flashbacks to my Digital Image Processing course. Man, I had a blast with this kind of stuff
A remarkable understanding to appreciate whether or not, how the conversion process to JPEG takes decision of how the human eye accepts what it is seeing.
I remember when JPEG first came into existence and it would take forever to compress and decompress that you would see the image go from a pixely mess into a nice image. This was the only format of image shared across BBS's over dialup, that and GIF. Bitmaps (BMP's) could be found rarely but it would take a decade to download. This by far is the most handy format for quickly sharing images.
JPEGs going from a pixely mess to the proper image is because the image is a Progressive JPEG and not a Baseline JPEG.
Baseline JPEGs are displayed line by line as they are downloaded while Progressive JPEGs contain a number of Level of Detail versions of the image. Progressive JPEGs will load and display the lowest LoD, and then when a higher LoD has finished downloading, it will switch to it, and it does this switching through the higher LoD images until the proper image is downloaded and displayed. Progressive JPEGs are larger than Baseline JPEGs because of the additional LoD images.
@@Oshroth Yes. The many LOD's were useful over slower connections as they showed you roughly what the image was quickly so you can make a choice without having to wait for the full image to load. This was back when browsing a webpage was faster cause they optimized it for speedy loading of the text and progressive loading of images.
"Can you see the difference?" - Actually not, the video is compressed as well
This comment is to tell you that I love what you have done. Thankyou for including Tom Scott and Blender.
Excellent tutorial on JPEG encoding and decoding algorithms. I learnt a lot from this video.
16:28 Well, vector images are a different beast altogether. They aren't rasterised, so _any_ bitmapping format will result in quality loss, even bmp and png. Vectors are made to be scaled and work by having nodes and lines that make up the image.
Instead, what you probably meant, was that jpg doesn't perform well on digital images, such as pixel art, or anything with sharp contrast, such as text overlaying on any other image.
Jpg also isn't preferred when working with intermediate copies. If you have a photo that you want to use in a video, for example, where it may undergo additional colour grading, you do not want to use a jpg image. This is because any additional grading can highlight artefacts, and because the image would be compressed twice; once by the jpg algorithm and again by the video compression.
I think he might have meant when saving a vector image to a bitmap format, to retain alpha.
I think what he meant was that when rasterising a vector graphic (which you literally have to do to view one) JPEG is a bad choice.
@@LucienHughes Yeah, but any format is a bad choice for saving vectors, except for vector formats.
You rasterise it for viewing (unless you use a vector display, like an analog oscilloscope), but you can still scale it without losing detail. You can't do that with a bitmapped format, not even png.
@@DaedalusYoung Distance fields are an interesting compromise between vectors and bitmaps. Some game developers use that for fonts for example.
How about TIFF?
Ah, JPEG. The greatest friend of a web designer, the worst enemy of a digital artist.
webp is worse... XD
or fake-transparent png's
@@Mic_Glow omg I really hate those types of pngs like why just why
The worst enemy of a photographer who is asked to post-process jpeg images from cell phones and make them look as if the scene was taken with a DSLR with a proper lens and saved as RAW data. A nightmare.
Mind-boggling amount of work goes into things we take for granted!
Learned to appreciate the engineering behind the jpeg today. Very cool stuff!
as a person working with image processing, this is absolutely fascinating. Also, that is a great explanation of DCT!
I'm a programmer and I've never bothered deep diving into jpeg, always treating it like some kind of magic.
This just cleared my mind on everything about it in less than 10 minutes. I can now explain it to people, and it's almost worrying how fast this went.
Damn, you're good.
Amazing content, as usual ! This channel is pure gold !
Thank you very much. Can't believe the idea can be explained in such a straightforward way! Thanks!
You can clearly see those artifacts in H.264 compression in an MKBHD video where he re-uploaded the same video for 1000 times.👍
I'm glad you mentioned Tom Scott when talking about Hoffman algorithm, I watched that video, and also the interframe compression that makes any confetti video look ugly😂
The information and the presentation is just amazing! Great work!
Thank you for making this video.
I'm actively working on a project that I need to understand and recovery the JPEG algorithm for.
While I've found web articles about the algorithm, this video clarifies so many points I couldn't get from said articles.
I must say that 10:1 compression ratio using JPG is quite impressive. For special images that are easily prone to artifacting, I just use the highest quality setting and that pretty much does the "trick". It would have been nice had they included a lossless option in original JPG for people that want a mathematically identical representation of the original image, but 1/2 to 1/3rd the size of a 24 bit RGB image. So basically getting it down to the filzesize of 8 or 12 bit color, but still retaining the original 24 bit color information.
you can compress .pngs though
This video is great and I would really like to see a follow up video for another popular image format called PNG, which is orders of magnitudes better than JPEG for vector images. The reason being that it is so widely supported while having other strengths and weaknesses compared to JPEG.
Yes. A similar video on PNG would be great!
run length encoding
more widely supported but blur
png is a raster image format and not a vector image format. svg is a vector image format.
@@joshix833 But for being a raster format, it's fantastic at compressing vector-type images. No compression artifacts, and incredibly small file sizes
This video is beyond amazing and more than what I could ever want as others have more accurately and eloquently described. I thoroughly enjoyed this video and watched it over again to better absorb the information. But I must say that I sifted through comments and I don't think anyone mentioned that those tulips are daylilies! Haha just an insignificant detail that has no bearing on the point of the video. Totally subscribed 👍 😀
this is brilliant for someone who's only "hobby-ist" computer literate like myself. thank you for breaking it down!
Can't wait for the x264 and x265 video, how P (Prediction) frames, I (Intra Frames) and B (Bidirectional Frames), AQ-Mode, AQ-Strength, block-size, B-Pyramid, etc., options work, how well it compresses data and why sometimes x264/x265 compress dark scenes badly along with artifacts or why x265 tends to blur out certain scenes while failing to apply proper DCT and quantization to such scenes properly to try and do an effective job at the compression or blur without any perceptive detail loss (which I believe such codecs need improvement in such area). Really need in-depth research video on it for innovation of future technologies!
Well put together and very structured. I'd be interested to know what caused the change in the audio quality on the voice over (example 7:44 / 7:46).
Those parts were probably recorded at a separate time, with a different microphone and/or settings. It's noticeable enough that it honestly kinda distracts me.
@@Sukigu That part on separate times is obvious, I noticed this with other channels as well. There is an unintentional sound effect on the 'second take' that i can sometimes hear even in movies (like a sort of high frequency tremelo on male voices) and i always wondered what caused it.
This is the clearest, yet most comprehensive, explanation of JPEG compression that I've seen so far. I finally feel like I understand it. Thank you!
One small quibble that is unrelated to the topic of JPEG compression:
The video suggests that the rod cells in the human eye act something like the "luminance" channel of human vision to the cone cells "RGB" channel. The reality is quite a bit different.
Rod cells are the "low light level" cells of the human eye, and do not contribute much to our visual perception in bright conditions. Indeed, bright lighting conditions, such as those of a regular phone or computer screen, are bright enough to overwhelm the rod cells and stop them from contributing a signal to our vision. They essentially "turn off" in such conditions. Conversely The cone cells are the "bright light level" cells and do not perform well in low light conditions.
Also, the rod cells, though more numerous, do not work in isolation. In low light conditions, the human eye performs a kind of "binning" with rod cells, where it combines the signal from a large number of individual cells to produce a signal that passed on to the brain. Indeed, this binning can combine the light detection capabilities from so many cells that the resolution that we get in low light conditions (where the light-loving cone cells lose sensitivity) is far lower than one would expect given the number of cells involved. Try reading a printed page by moonlight alone and you'll see what I mean. (There's"temporal" binning as well, where the early processing of the eye's signal combines the light over a longer period, up to about 1/6th of a second, to produce a stronger signal and any movement during that time will "smear" the image.)
So, when dealing with anything displayed on a computer screen, it is the "bright light" cone cells which do the heavy lifting. This does not affect the sharpness of our vision, however. That there are only "about 6 million cone cells" (and astonishingly few "blue" cone cells, BTW) is made up for by the fact that they are largely crammed into a tight area at the center of our vision known as the "fovea". The fovea covers only a few degrees of our vision- so the resolution in that region is quite high. Indeed, I've seen estimates that suggest if we spread the resolution of our fovea over our entire visual field, the result would be the equivalent of a 100 megapixel image or more. (TV manufacturers set their recommended viewing distance based on this sort of calculation, BTW.)
Our perception of sharpness over a broad image is created by the fact that our eyes dart around (that is, perform "saccades") picking up bits and pieces of an image and assembling them in our brains. The parts of the image that our eyes do not land on are "filled in" with plausible sharpness or ignored.
Try reading the paragraph above this one while staring fixedly at the period at the end of this sentence. (Don't cheat!) If you're a normal human being you can't do it, despite the fact the text above this paragraph is quite close to the center of your vision. Your eyes do not have many cone cells outside the range of that period and there's simply not enough retinal resolution there to make out the fine details of printed letters. You do not sense anything amiss, however, because your brain "fills in" the blurry areas with a "sense" of sharpness.
The intensity levels are simply a measurement of the intensity of each cone cell's intensity- with a quite a bit of "local contrast enhancement" (a very interesting process, which would require many paragraphs of explanation to outline) done by the retina.
Incidentally, the cone cells are not truly RGB (red, green, blue)- in that they have peak sensitivities evenly distributed across the visible spectrum. They are, instead, more like Y-YG-B (yellow, yellow-green, blue), but, with three different ranges of peak sensitivity, they are able to unambiguously distinguish all the colors of the rainbow.
The rest of the details in the video which deal with our perception of spatial resolution and frequency is on point. It just doesn't have anything to do with the distinction between rod and cone cells.
Stunning explanation of a complicated technology, Thank you.