In transcoding, it is well known that refinement of the motion vectors is critical to enhance the quality of transcoded video while significantly reducing transcoding complexity. This paper proposes a novel cost model to estimate the rate-distortion cost of motion vector composition in order to develop a reliable motion vector re-estimation method that has reasonable computation cost. Based on a statistical analysis of motion compensated prediction errors, we design a basic form of the proposed cost model as a function of distance from the optimal motion vector. Simulations with a transcoder employing the proposed cost model demonstrate a significant quality gain over representative video transcoding schemes with no complexity increase.
All Science Journal Classification (ASJC) codes
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence