Curvature-Based Real-time Brightness Adjustment for Ultra HD Video

In conditions such as inclement weather or in-sufficient lighting at night, video captured by camera equipment may be insufficiently bright and have low contrast. With the popularity of ultra-high-definition video images, its ultra-high resolution makes the performance requirements of video processing algorithms more and more stringent. Aiming at these problems, this paper proposes a curvature-based real-time brightness adjustment algorithm for ultra-high-definition video. The algorithm is implemented in two steps: global brightness adaptive enhancement and local contrast adaptive enhancement. The experimental results show that the algorithm proposed in this paper not only highlights the details of low-brightness areas of video images, but also avoids excessive enhancement of high-brightness areas. It is superior or comparable to the comparison algorithm in both subjective visual effects and objective evaluation indicators. In addition, because the algorithm in this paper is simple and easy to implement, it can be easily implemented in parallel, and can be applied to real-time processing of ultra-high-definition video, which has high practical value.