Adaptive Bitrate Selection for Video Encoding with Reduced Block Artifacts

Blocking artifacts, commonly introduced during video encoding, are one of the major causes of reduced perceptual video quality. The trade-off between these artifacts and bitrate can be improved by adaptively selecting frames from a set of video copies encoded at different bitrates, prior to actual video encoding. We propose a new direction of constructing mixed bitrate video based on content-based image analysis on each video frame, which was posed as a problem of pre-analysis for the final video encoding step. The proposed method consists of the following steps: First, we define a simple and fast impact metric in order to identify the blocking artifacts in each frame of multiple videos, encoded at different bitrates. Based on the impact metric, we generate a blocking artifact density functions for the available bitrates, on the whole video. Finally, we define and optimize our objective function from the blocking artifact density functions in order to select a bitrate with minimum perceptual blockiness and file size for each frame. We validated our method throughout multiple types of videos, showing improved visual quality for the same file size based on commonly used quality assessment measures, such as MSU blocking, MSU blurring, SSIM, 3SSIM, and stSSIM. The reduction rates of average file size and average blocking artifact were about 4.9% and 8.3% over maximum bitrate encoding, respectively.