What specific characteristic of iPhone's computational photography features, like Night Mode, allows it to capture usable images in light levels where a traditional single-exposure camera would produce only black?

The specific characteristic of iPhone's computational photography features, such as Night Mode, that allows it to capture usable images in extremely low light is its ability to perform multi-frame capture combined with intelligent computational stacking and merging of those frames. In conditions where a traditional single-exposure camera would produce only black, it lacks sufficient light (signal) in a single capture to overcome sensor noise, resulting in an undifferentiated dark image or one overwhelmed by noise if ISO is boosted. iPhone's Night Mode addresses this by first rapidly capturing a sequence of multiple individual, relatively short exposures. These individual short exposures are crucial because they minimize the risk of motion blur from camera shake or subject movement, which would be unavoidable with a single, long exposure required in very low light. After capturing these frames, the device's software performs precise digital alignment of the images, correcting for any slight shifts or movements between captures. Following alignment, these multiple frames are computationally stacked or merged. During this process, sophisticated algorithms analyze and average the pixel data across all the aligned images. Random noise, which appears differently in each individual frame, tends to cancel itself out when averaged. Conversely, the actual light information and consistent details of the scene, which are present in all frames, are reinforced and accumulated. This effectively increases the overall signal-to-noise ratio, synthesizing a final image that contains significantly more light information and detail than any single captured frame, without introducing the motion blur or excessive noise that would plague a traditional single-exposure camera under the same conditions.