'Improve the User Experience in Your Mobile App by Using Low-light Enhancement Tech' ai mobileapps
. Both the AI-powered technologies require face recognition abilities based on video inputs, and the output effects rely heavily on the quality of video input.
a) The framework and models are pretty big; b) The computational volumes are large; c) The power consumptions are significant.2) Common Issues of Traditional Algorithms a) Not all video pixels should be brightened since some are already light enough. We will scan through a video frame by frame, and find pixels of different categories: Some video pixels are fairly light and need no brightening.
We extract the 2D/3D LUT for runtime table lookup purposes. The overhead of this lookup table is very small, and the approach has demonstrated great performance.The algorithm will scan video pictures, and evaluate the lightness levels of different areas. We brighten the areas that are low-light but contain valid information and leave those areas that are already light enough.
Detecting the changes is heavy computational work, which will slow down processing speed and introduce latency. Also, detecting algorithms is complicated and its judgment could be wrong pretty often.
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