Computational photography is transforming the way photos are made. Here's a primer on what it is.
There’s a reason why my iPhone is often the only camera I’ll carry with me. Its imaging quality allows me to take good photos without having to carry any additional gear.
A portrait without portrait mode and a portrait with portrait mode on to simulate a shallower depth of field . This all happens quickly in most smartphones because a smartphone camera is always imaging when the camera app is in use. Otherwise, the live “preview” couldn’t be shown. Only the images that you press the shutter button for are saved to your device’s photo album, but there is always a buffer of photos that your smartphone hangs onto for a little bit and then discards.
A slide shown during an Apple launch presentation that shows how the iPhone’s image signal processor and Neural Engine automatically enhances each photo captured. Image: Apple.In computational photography, image-making is often an additive process. In other words, one image is rarely the product of a single image. Rather, an image is a combination of many different images with different parameters. Pixel shifting is another example of this.
of a scene captured by a Sony mirrorless camera using a single shot , a 4-image pixel shift composite , and a 16-image pixel shift composite . Click to enlarge. Image: Sony.Very basically, pixels help capture light, and larger pixels capture more light. However, smartphone cameras need to be small, and therefore their pixels need to be small.
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