The Pixel 7 series introduced an enhanced Night Sight feature, and as promised, Google is now delivering this advanced camera functionality to the Pixel 6 lineup. While the new zoom bar seen on Pixel 7 devices hasn’t made it to the Pixel 6, the Night Sight improvements are still significant.
Night Sight upgrade: Faster and sharper
The updated Night Sight now requires 50% less exposure time, resulting in faster captures and reduced blur. Images are noticeably sharper, showcasing the improvements Google has made. Alongside the dedicated night mode, Google also refined HDR+ with Bracketing to minimize noise.
Pixel 6 owners will find a new toggle when using Night Sight, allowing them to choose between a fast mode with less exposure or a slower one with more exposure. Depending on the lighting conditions, exposure times range from 2 to 6 seconds. In well-lit environments, the 6-second exposure won’t be necessary.
The Google Camera version 8.8 update, which includes these enhancements, is being rolled out widely. Users can either update through the Play Store or wait for the automatic update to arrive.
What is Night Sight?
Night Sight is a groundbreaking feature introduced by Google in their Pixel smartphone lineup. This innovative camera mode is designed to enhance low-light photography, allowing users to capture stunning images even in challenging lighting conditions. By leveraging computational photography techniques, Night Sight significantly improves image quality and detail when shooting in dim environments.
One of the primary challenges in low-light photography is capturing enough light to produce a well-exposed image. Traditional smartphone cameras often struggle in these situations, leading to grainy, blurry, or underexposed photos. Night Sight addresses this issue by taking multiple exposures of the same scene and combining them into a single, well-lit image.
The magic of Night Sight lies in its ability to intelligently adjust various camera settings, such as exposure time, ISO, and white balance, to achieve optimal results. It uses machine learning algorithms to analyze the scene and determine the best settings for each shot. This process helps minimize noise, improve color accuracy, and increase overall image sharpness.
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