How the Kirin 970 uses Handheld Super Night Mode to Take Better Photos at Night
When it comes to smartphone photography, the most challenging shots are always going to be night shots. Situations with limited light most often result is grainy unusable photos for devices with weaker cameras. The Kirin 970’s AI chip helps to solve this issue with “Handheld Super Night Mode”.
One way to achieve better night shots is to set your phone on a tripod and let your camera use a longer exposure and higher ISO. This is a bit inconvenient as most people obviously wont be walking around with tripods. To solve this issue, Honor uses the Kirin 970 to add “Handheld Super Night Mode” to their phones. This mode lets you take better night shots without having to setup any equipment.
Handheld Super Night Mode works by using powerful AI algorithms, and the quick processing ability of its Kirin 970. There are several techniques used to enhance your night time photos.
AI Detection of Handheld State
One of the key factors of Handheld Super Night Mode is how the phone uses the AI chipset to detect any hand-held jitter of the phone. To realize accurate and efficient detection, the AI system collected and analyzed tens of thousands of data records reflecting different types of photographers and their camera and tripod usage methods, designing a machine learning logic to understand their habits. As a result of implementing this massive amount of data, the Kirin 970 is able to detect when Handheld super night mode is needed in 0.2 seconds. Using this data, the average users is now able to take better night shots without having to use a tripod.
AI Photometric Measurement
The AI photometric measurement system controls the camera’s light intake. After you tap the shutter button, The AI will automatically set the exposure and number of frames based on the lighting scenario, brightness of the preview image, distribution of light sources, and jitter.
AI Image Stabilization
After all of your frames are captured from your night shot, they are merged into a single image. It is common that surring this process, night shots often turn out blurry. To avoid this, before the synthesizing process takes place, the AI the clearest frames and discards any of the bad ones. The clearest frames are used as the standard for the image, while the other frames that the AI has not discarded are automatically aligned. The AI-powered Kirin 970 chip detects feature points within each frame, matching these points and aligning them to to produce the cleanest image possible.
The final step in Super Night Mode is image synthesis. For this step, customized algorithms have been computed for the AI system to increase the number of short-exposure frames in bright areas to avoid overexposure and the number of long-exposure frames in dark areas to improve detail retention. Frame differences are detected pixel by pixel. If differences are large, AI determines that alignment failed around the edges and conducts correction and repair to ensure the edge regions are still crisp and sharp enough after synthesis. Noise reduction is performed on multiple frames, thereby improving the image’s signal-to-noise ratio, and achieving a clearer, cleaner, and brighter night shot.
Photos Taken on the Honor 10
These photos were taken on the Honor 10, with the Kirin 970 AI chipset using Super Night Mode.
We thank Honor for sponsoring this post. Our sponsors help us pay for the many costs associated with running XDA, including server costs, full time developers, news writers, and much more. While you might see sponsored content (which will always be labeled as such) alongside Portal content, the Portal team is in no way responsible for these posts. Sponsored content, advertising and XDA Depot are managed by a separate team entirely. XDA will never compromise its journalistic integrity by accepting money to write favorably about a company, or alter our opinions or views in any way. Our opinion cannot be bought.
Want more posts like this delivered to your inbox? Enter your email to be subscribed to our newsletter.