Midweek mobile 12

Push anything to extremes and flaws will begin to show up. Cell phone cameras now boast photos with around 100 million pixels, but taken with toy lenses a few millimeters across. The images that the phone gives you are the result of statistical computations based on fuzzy data. The enormous amount of computation needed for building an image (yes, images are now built, not captured) drains your phone’s battery faster than other uses would. How do you actually get to see the flaws of the optics? One way is to push the camera to extremes. Here I look at low-light photography, so that the camera’s ISO boost begins to amplify the problems that the image always has.

The featured photo used the 4.7 mm lens at the back of my phone, and used an exposure of 1/13 seconds (this means averaging over an enormous number of captures). The original image had 9248 pixels on the long side. When I compress it down to 1250 pixels for wordpress, the result is a crisp picture. Examine it at larger scales though, and flaws emerge. The detail shown in the above photo takes a segment which is 830 pixels on the long side and compresses it to 640 for wordpress. The camera chose an ISO of 15047, and there is quite a bit of noise in the detail. You can see lens flare below the arch. Above the arch you can see some of the railing blown out. The pixels are saturated and nothing you do can bring information out of them. Elsewhere, the railings are full of digital artifacts such as aliasing.

• 

• 

In the slideshow above you see an even more extreme case. This is a photo taken in a dark wood on a new moon night looking for owls using flashlights (yes, this was how I spent my diwali). The camera chose an ISO of 17996 and an exposure of 1/10 seconds. In the most contrasty bits of the photo you can easily see the noise in the image even without sliding into the detailed view. The lens flare in the detail looks cloudy; the AI has tried to erase it without success. It has performed surprisingly well in the face. I’m really impressed with the technique of computational super-resolution that it applies.

• 

• 

I close with a less extreme example from earlier in the evening. Here the software chose an ISO of 844 and an exposure of 1/25 seconds. Details are less grainy, as you can see when you zoom into the picture. The road signs are quite clear, if a little too dark to read easily, but the darker areas of the photo have clear digital artifacts, some of which you can see in the zoom. But you can see the liquor shop in its prize location at a crossroad blazing with light, open to its business of making the roads less safe to drive on.

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.