Midweek mobile 15

Modern phone cameras get sharp and bright images with awful lenses and jokes of sensors. The most important aspect of the images is that they are usually viewed on the small screen of a phone. A quick search led me to an estimate that people take 4.7 billion photos every day. Be suspicious of such facile estimates. But it is clear that far less than a percent of a percent would be viewed on a large screen, where defects can show.

• 

• 

• 

• 

I stress tested my phone camera in exactly this way. My phone has a sensor with 4608 x 3456 pixels. I reduced it to 1667 x 1250 pixels for the leader photo. That looks good. But I asked what it I looked at it pixel for pixel: one pixel of the sensor for every pixel on the screen (1:1). I did that in the most detailed photo in the slideshow above. The next one compressed 4 pixels of the photo into one on the display (4:1), the next 16 pixels of the photo for one on the display (16:1), and the next (the featured photo) is shown 32 pixels per pixel of display (32:1). But for the post I compressed these views a little more; the closest is at 9:1, the rest are 36:1, 144:1 and 288:1. The result begins to show digital artifacts in the 9:1 view, although they are not overwhelming (at 1:1 they are unmistakable). Of course, I can’t predict what screen you’ll see them on, but if you have a choice looking at them on the biggest screen you have would be interesting.

• 

• 

• 

• 

On a whim I took a photo of a beetle and gave it the same treatment. Here you see the views in the ratios 9:1 (nine pixels of the photo to one of the display), with the successive frames showing 36:1, 144:1 and 288:1 compressions. It is only the last which looks sharp. On my phone the display is even smaller, so the image looks much sharper. But why this big difference between flora and fauna? I compared the exposure first. The flowers are taken with an equivalent exposure of 1/100 seconds and ISO of 100; the beetle with 1/50 seconds and ISO of 223. This means that the number of frames which are superimposed to give the final image is twice as many in the second. Slight hand movements could create the effect that you see, but the phone must compensate for that. But the ISO is also a factor; you can see more “grain” in the image of the beetle. I think another important factor must be the contrast between the object and background. That’s much smaller in the second photo. I’ll try to explore this further.

If you want a moral, I would say “Don’t look a gift horse in the mouth.” Your phone does not replace a good DSLR in image quality. Be happy with what it shows on its small display.

Phone photography changes our expectation of the interaction of camera hardware and image so dramatically that it is worth rethinking what photography means. I intend to explore this a bit in this series.

Midweek Mobile 1

Night time is the worst time for photography if you have a tiny lens. Anticipating crowds and rain on the eve of Independence Day, I went out to get some street photos, but only took my mobile phone. It does a lot of computation to deduce the shapes and colours of what is recorded. With all that computation that goes on between the light hitting the sensor and an image being saved in memory, newer and faster computational hardware has an advantage.

But did these results actually improve over the physical limitations of the small lens? In one sense they did. If and when the sensor and imaging involve chemistry, a small lens exposes less of the chemical on the film. The result was that photos look dim. We are used to saying under-exposed for such photos. The only way to make the image brighter would then be to expose the photo for longer. But that creates a problem we call motion blur. With computation sandwiched between the sensor and image, there is a third way: the brightness can be amplified. I saw that The Family gets a much brighter image with her phone than I do, because her camera software is set to amplify more. So the problem of under exposure is replaced by that of digital noise: when you amplify, both signal and noise are usually amplified together. Motion blur can still be seen though, in the featured photo, for instance.

In another sense, the limitations of a small camera remain. A lens which is half a centimeter across cannot see details smaller than a couple of millimeters at a distance of ten meters. But this fundamental limit of resolution is reached only when the sensor collects light forever. With limited exposure the resolution drops by a factor of ten or hundred. So the image always has to balance motion blur against lens resolution. You can see this at work (at least on a large screen) in the photo above. The scene was well lit, the camera was not in motion, but the image is not awfully sharp. The computational hardware has prioritized freezing the movement of people by sacrificing the light needed for better resolution.

I suppose these photos look sharp and bright enough on phones and tablets to gather likes on instagram and tiktok. Perhaps you are in a minority if you view them on larger screens. As it turned out, it didn’t rain, so I could have taken a better camera with me. But technique is what you develop when you have limitations. A mobile phone is less obtrusive when you want to take street photos, so it is a good idea to start using it more widely for serious photography.

Phone photography changes our expectation of the interaction of camera hardware and image so dramatically that it is worth rethinking what photography means. I intend to explore this a bit in this series.