Lightweight content-adaptive coding in joint analyzing-encoding framework

A novel joint analyzing-encoding framework is proposed in this paper. With this framework, the video analysis and the video coding can be integrated together, which can decrease the computational complexity of the video process system due to the obtained shared information. A lightweight content-adaptive video coding scheme can be achieved by using the presented framework for H.264 standard. The side encoding information, including motion vectors (MVs) and sum of absolute differences (SADs), can be used to reduce the computation cost of the moving region analysis. First, the rectangular shape and the displacement information of the moving region in the current encoded frame are obtained by employing a robust binary detection method, which is based on the adaptive threshold and the fast components labeling algorithm. Then, the rectangular shape information of the next frame is achieved by using a simple but effective prediction method, which considers the principle of the temporal motion constraint. Finally, a motion importance mask map (MIMP) is obtained according to the predicted rectangular shape information. Meanwhile, a category of frequency coefficient suppression(FCS) technique in the transform domain is presented to avoid the use of the complex MB-layer rate control method. With MIMP and FCS, a lightweight content-adaptive video coding scheme is realized based on a simple frame-layer rate control method. Experimental results show that the proposed scheme can detect and predict the moving regions fast and improve the objective/subjective visual quality significantly for the moving regions.

[1]  Robert J. Safranek,et al.  Signal compression based on models of human perception , 1993, Proc. IEEE.

[2]  Chun-Jen Chen,et al.  A linear-time component-labeling algorithm using contour tracing technique , 2004, Comput. Vis. Image Underst..

[3]  Anthony Vetro,et al.  Surveillance System with Object-Aware Video Transcoder , 2005, 2005 IEEE 7th Workshop on Multimedia Signal Processing.

[4]  Tihao Chiang,et al.  A new rate control scheme using quadratic rate distortion model , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[5]  Henrique S. Malvar,et al.  Low-complexity transform and quantization in H.264/AVC , 2003, IEEE Trans. Circuits Syst. Video Technol..

[6]  Shuozhong Wang,et al.  Moving traffic object retrieval in H.264/MPEG compressed video , 2006, SPIE Defense + Commercial Sensing.

[7]  Hwangjun Song,et al.  A region-based H.263+ codec and its rate control for low VBR video , 2004, IEEE Transactions on Multimedia.

[8]  Yu Sun,et al.  Region-based rate control and bit allocation for wireless video transmission , 2006, IEEE Transactions on Multimedia.

[9]  Fatih Porikli Real-time video object segmentation for MPEG-encoded video sequences , 2004, IS&T/SPIE Electronic Imaging.

[10]  Cedric Nishan Canagarajah,et al.  A perceptually optimised video coding system for sign language communication at low bit rates , 2006, Signal Process. Image Commun..

[11]  Zhengguo Li,et al.  Conversational Video Communication of H.264/AVC with Region-of-Interest Concern , 2006, 2006 International Conference on Image Processing.

[12]  Zhengguo Li,et al.  A Novel Rate Control Scheme for Low Delay Video Communication of H.264/AVC Standard , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[13]  Homer H. Chen,et al.  Frame-Layer Constant-Quality Rate Control of Regions of Interest for Multiple Encoders With Single Video Source , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[14]  Haohong Wang,et al.  Real-Time Region-of-Interest Video Coding Using Content-Adaptive Background Skipping With Dynamic Bit Reallocation , 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

[15]  Ja-Ling Wu,et al.  Content-based rate control scheme for very low bit-rate video coding , 1997 .

[16]  Do-Kyoung Kwon,et al.  Rate Control for H.264 Video With Enhanced Rate and Distortion Models , 2007, IEEE Transactions on Circuits and Systems for Video Technology.

[17]  R. Venkatesh Babu,et al.  Video object segmentation: a compressed domain approach , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[18]  Ankush Mittal,et al.  High Quality Compression of Educational Videos Using Content-Adaptive Framework , 2006, ACCV.

[19]  Jordi Ribas-Corbera,et al.  Rate control in DCT video coding for low-delay communications , 1999, IEEE Trans. Circuits Syst. Video Technol..

[20]  Nele Van den Ende,et al.  Towards Content-Aware Coding: User Study , 2007, EuroITV.

[21]  Zhi Liu,et al.  Moving object segmentation in the H.264 compressed domain , 2007 .