Sorry, you need to enable JavaScript to visit this website.

Multiple Linear Regression for High Efficiency Video Intra Coding

Citation Author(s):
Zhaobin Zhang, Yue Li, Li Li, Zhu Li, Shan Liu
Submitted by:
Zhaobin Zhang
Last updated:
7 May 2019 - 2:19pm
Document Type:
Presentation Slides
Document Year:
2019
Event:
Presenters:
Zhu Li
Paper Code:
3492
Categories:
 

In video coding frameworks, the essence of intra coding is leveraging the spatial correlation within a frame to remove redundancy thus achieving compact transmitting data. With modern video acquisition devices improvement, more high-definition videos emerge into people’s lives which has set a new challenge for high-efficiency video coding. In this paper, we propose a novel intra video coding scheme based on Multiple Linear Regression (MLR), named Multiple linear regression Intra Prediction (MIP). Instead of predicting pixel values by extrapolating, we try to exploit the potential capability of
homogeneous regression method. The proposed method has a very concise and neat design yet achieves better performance compared with High Efficiency Video Coding (HEVC) reference software anchor. The experimental results demonstrate the effectiveness of the proposed method and provide interesting insights for further exploiting the capability of conventional algorithms for video coding when many people favor deep learning-based approaches.

up
0 users have voted: