[TechSpot] Samsung's plans to kill the notch: Yes, please. - Page 3 - Overclock.net - An Overclocking Community

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[TechSpot] Samsung's plans to kill the notch: Yes, please.

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post #21 of 36 (permalink) Old 10-22-2018, 11:34 AM
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Quote: Originally Posted by ryan92084 View Post
Agreed, I don't undertand the notch lovers or haters. My essential has one and i really couldn't care less about its existance. Curved edges however are the bane of many cases and screen protectors and need to be toned down.
Exactly. I don't bother with the tempered glass protectors anymore. Had 2 simply pop off the phone (I have an S9+), fall on the floor and shatter. My mom has a Pixel 2 XL and she went through 3 of them, same thing.

I just now get cheap $15 cases on Amazon that come with it's own screen protector that works with the case. Just got a new one this weekend and it's actually pretty nice compared to the $50 case I had before.When it gets all scratched up, I'll just replace the whole thing.

Really have never figured out how the curved edge screen was supposed to be of any value as an end user.

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post #22 of 36 (permalink) Old 10-22-2018, 04:51 PM
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So it looks like they're putting a really small camera in whats left of the bezel?

I thought they were doing something ingenious with OLED, since it's per pixel based lighting, dim out a notch when the camera is activated or even physically move the OLED's within the phone when the camera is on.

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post #23 of 36 (permalink) Old 10-22-2018, 04:52 PM
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Quote: Originally Posted by Avonosac View Post
You wouldn't need to, just pulse them off when you're capturing a picture, with enough sensors to fill in the blind spots the camera would work just like your own brain does filling in your blindspot.
I'm not really sure what blindspots you're talking about since the OLED panel will be near completely (or basically completely) transparent. Cameras don't work like the human brain and don't exhibit persistence of vision. Perception/the human brain is analogous to postprocessing.

If you're saying turn off a small pattern of pixels (like say some checkerboard pattern), the photodiodes under the LEDs are still likely to clip due to the light from the adjacent pixels since there isn't a light pipe/channeling structure.

You're still going to need pretty high shutter speeds unless the phone uses a very low PWM frequency (voltage control is quite difficult to do with LEDs due to their non-linear nature so PWM is preferred) if it's going to be unnoticeable.

Currently most OLED displays in phones (iPhone X/XS/XS Max, Samsung's own flagships, etc.) use a PWM frequency of about 200-250Hz which is quite low. 1/200 and 1/250 shutter speeds at most ISOs will yield a good or decent image in most decently-lit and well-lit scenarios. 1/500 and above shutter speeds will usually require very good lighting conditions or very low noise and some post processing to get a good image. Good chance this frequency will go up as pixel response times improve in the interest of making the PWM switching imperceptible to human eyes.

Last edited by HybridCore; 10-22-2018 at 05:34 PM.
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post #24 of 36 (permalink) Old 10-23-2018, 08:13 AM
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Quote: Originally Posted by CynicalUnicorn View Post
Spoiler!
It depends entirely on the switching speed being high enough which I assume would be simple, which I highly doubt the brain wouldn't fill in as it currently does on screen dimming and strobing display backlights.

Quote: Originally Posted by HybridCore View Post
Spoiler!
The blind spots would be the pixels which as you point out are only mostly transparent. The point wasn't that cameras currently work like persistence of vision in the human brain, which at best the explanation was an analogy, but that you could use other cameras and neural networks to fill in the blind spots. Cameras currently don't work like this because not many cameras intentionally obfuscate the view in front of the lens.

You are going into a lot of the details to work out, but it's kind of irrelevant because this literally is the only way to prevent the sensor(s) being dazzled with the displays input light.


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post #25 of 36 (permalink) Old 10-23-2018, 06:38 PM
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No notch here, don't need Samsung, most other phones have no notch for decades.
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post #26 of 36 (permalink) Old 10-23-2018, 09:00 PM
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Quote: Originally Posted by Avonosac View Post
The blind spots would be the pixels which as you point out are only mostly transparent. The point wasn't that cameras currently work like persistence of vision in the human brain, which at best the explanation was an analogy, but that you could use other cameras and neural networks to fill in the blind spots. Cameras currently don't work like this because not many cameras intentionally obfuscate the view in front of the lens.

You are going into a lot of the details to work out, but it's kind of irrelevant because this literally is the only way to prevent the sensor(s) being dazzled with the displays input light.
Ah I see. I don't think the blind spot issue is a problem though because that's supposed to be the problem Samsung solved here: that their OLEDs are effectively clear and they can use what we can just best guess as lens correction algorithms (for the distortions caused by the pixel assemblies), not neural networks to fill in things where the information didn't exist to begin with. Not blind spots, rather warped spots.
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post #27 of 36 (permalink) Old 10-24-2018, 03:07 PM
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wow, so innovative from Samsung

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post #28 of 36 (permalink) Old 10-25-2018, 04:07 PM
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Quote: Originally Posted by HybridCore View Post
Ah I see. I don't think the blind spot issue is a problem though because that's supposed to be the problem Samsung solved here: that their OLEDs are effectively clear and they can use what we can just best guess as lens correction algorithms (for the distortions caused by the pixel assemblies), not neural networks to fill in things where the information didn't exist to begin with. Not blind spots, rather warped spots.
Yea, I mean we could get into the semantics if you want to disagree but it's a distinction without a difference. Those lens correction algorithms are either neural networks or psuedo-neural networks to perform image processing from imperfect data.

EDIT- BTW, this is exactly how many Satellites image processing works, they use video sensors instead of still image sensors, with different focal points and lenses to construct still images because it's pretty hard to take a picture of a fixed point going 7.8kM/s.



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post #29 of 36 (permalink) Old 10-25-2018, 06:41 PM
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Quote: Originally Posted by tpi2007 View Post

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I don't think that the author of the article realizes the insidious implications that this has to whatever little shred of privacy people have left. Also apply this to laptops and smart TVs and home assistants and smart fridges and car infotainment systems and you won't be able to cover the camera anymore without blocking part of the screen. The right way to go if they really want more screen real estate is a pop-up camera (ideally make it for both front and rear cameras in smartphones).
Ohh man I hope they patent this for a million years so I know what company to never buy from and I'll be safe from those I do!!!!

I just can't wait to have to root out and mod my screens to disable hidden cameras.

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post #30 of 36 (permalink) Old 10-26-2018, 07:19 PM
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Quote: Originally Posted by Avonosac View Post
Yea, I mean we could get into the semantics if you want to disagree but it's a distinction without a difference. Those lens correction algorithms are either neural networks or psuedo-neural networks to perform image processing from imperfect data.

EDIT- BTW, this is exactly how many Satellites image processing works, they use video sensors instead of still image sensors, with different focal points and lenses to construct still images because it's pretty hard to take a picture of a fixed point going 7.8kM/s.
Lens correction works differently because it's not guessing. It's remapping points to a new location to cancel out the effects of distortion in the lens. Neural networks make guesses and fill in information that didn't exist. They're very different beasts. One requires insane amounts of data to train the system and the other one is a much simpler set of transformations (albeit nonlinear).
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