Why the human eye still beats the camera

50:03I I I think that was pretty cool. This is quite nice. Okay. Um we've been focusing a lot on the photographs, but one thing that I don't want to leave out is the human observer. Yes. Okay? So, there are a lot of recorded observations. This is a photograph of I believe Commander Reid Wiseman just looking through the window and taking observations. They had iPads that, you know, cuz when you go to the through the far side of the moon and then the Earth is no longer in view, you can no longer communicate with Earth. But that doesn't mean that you're not going to be taking observations, right? You're going to be taking photographs and you're also going to be relaying

50:43observations about what your human eye is seeing. In some cases, the human eye is worse than cameras, but in a lot of other cases, the human eye is actually vastly superior to any digital camera that we have for deep space observation. The digital sensor has strong limitations. It has to do with the response. Okay? The digital camera uses CMOS sensors. And what it's doing is literally just counting photons and the photons have to excite the silicon atoms, the metal oxide silicon, that's what MOS is, metal oxide silicon. Uh it has to excite the atoms in the sensor to then produce some kind of digital fingerprint that we then record

51:26as data. The human eye uses rods and cones in our retina. The rods are really highly sensitive to low light and the cones are really high-resolution color vision. The big difference, though, comes in their response curve. This is the input-output relationship between how much light is coming in and what you perceive. >> Mhm. >> For a digital camera, how much light is coming in is exactly what you would perceive. If I have 10 photons that come in or 100 photons that come in, I would sense 10 times the brightness, 100 times the brightness, right? Human eye has a logarithmic response.

52:06Here's what that means. In the blue is your linear curve from a camera. If I have 20% of light coming in, I get 20% response. >> Mhm. >> 50% light coming in, 50% response. The human eye is a logarithmic curve, meaning lower light has a much higher >> Yes. >> output. >> Yes. >> Right? So, we are really highly sensitive to that low light condition. >> Shout out evolution. >> Especially It's Shout out evolution. Especially when it comes to going around the moon, being in the eclipse, the corona is going to be this faint glow around the moon. >> Mhm. >> The human observer can see a lot more >> Mhm. >> in real time than a camera ever could. >> Mhm. Mhm. >> Cuz we've had a billion years and a camera what? 100

52:47>> A camera yeah, you're right. >> Right. >> It might get quite nice. >> It might get quite nice, but so far >> Not yet. Not not yet. >> is This is one of those things where biology is just beating um hardware. >> I mean, that that's it's such an interesting cuz we talked about it earlier about this advantage of having what was it? 3 million 1 million 3 million ISO? >> ISO. >> Um on the D the Nikon D5. >> But even then >> Right. And and that's kind of the you know there's a je ne sais quoi right? About the the meat sacks that we're in. >> Yeah. >> Um and our ability to perceive through our core senses, not through uh

53:29how we are able to intuit like in our internal monologue and cognition, but literally just through the input sensors of our physical body. >> Yeah. >> Those input sensors are quite nice. Eyes are quite nice. Maybe the meat fingers could be a little bit better. It's it's it's low the the >> But the eyes are just like insane. And the other thing you might think is like, "Okay, well, if it's just an input-output thing, what if I just like mathematically make the curve the same?" >> Sure. >> Right? If the input is coming in, I could just do that. The other thing that the eye does is it operates via rapid micro movements called saccades. Because the eye, when it's focusing, your eye is not actually perfectly still. It's doing tiny movements.

54:09What the brain is doing is integrating all of those tiny movements into this fully formed conscious experience that we have. But what that means is your signal to noise goes up like crazy because you're doing tiny little movements and taking a bunch of photographs, you can think of, and then you're integrating that. There's a stabilizer in some sense. And so, if if at a particular angle there's like noise, if you if you look just a little bit of this way, just a little bit this way, the fact that the eye is doing these saccades and there's this non-linear integration that's happening in the brain, that's something that you can't replicate with just like straight hardware on a camera.

54:50>> We have the best image stabilization of all time. >> Yeah, it's ridiculous, right? And that image stabilization is creating more signal to noise, right? Right? It's not actually like trying to um like deal with >> stabilize the signal almost. >> Yeah, yeah. It's like when we think about image stabilization with our iPhone, for example, right? Like if we're taking video and we want to upload that to Instagram, there's like internal image image stabilization. But what that's actually doing is taking a a a really bad sort of jittery video and trying to do the best that it can. Here we're actually making it better. >> Right. >> The sensitivity is becoming better. >> Yes. >> Which is which is very non-trivial. It's it's it's quite a distinct difference. >> point. No, it's a really important

55:30point. And and it it that is, you know, I I there's a condition that I can't remember where the the eye movement is a little bit like it's above the baseline. >> Mhm. >> And so it's very visible when you look cuz when you look at somebody and you look at them in the eye. >> Yeah, you can't really tell. >> really tell. >> Yeah, but it's happening all the time. >> happen if it's happening all the time and it it's it's sort of why like you get sort of like you you don't you you'll you're not paying attention and you'll see something in the your periph. >> Yeah. >> And then you'll be like, wait, what was that? >> Yeah, because because it our eyes are and the algorithm in our brain is just so sensitive >> Right. >> to all kinds of stuff. Our algorithm in our brain is also really sensitive to change. >> Right. >> Okay? Like you see a static photo and

56:11then tiny bit changes the the brain is like, what was that? And as you were saying the the observations that the crew got is the first time in history they saw six sudden bright flashes of light on the lunar surface. >> Mhm.