In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on...In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on human visual saliency model in H.264/AVC. Firstly, we modifie Itti's saliency model. Secondly, target bits of each frame are allocated through the correlation of saliency region between the current and previous frame, and the complexity of each MB is modified through the saliency value and its Mean Absolute Difference (MAD) value. Lastly, the algorithm was implemented in JVT JM12.2. Simulation results show that, comparing with traditional rate control algorithm, the proposed one can reduce the coding bit rate and improve the reconstructed video subjective quality, especially for visual saliency region. It is very suitable for wireless video transmission.展开更多
The growing number of mobile users, as well as the diversification in types of services have resulted in increasing demands for wireless network bandwidth in recent years. Although evolving transmission techniques are...The growing number of mobile users, as well as the diversification in types of services have resulted in increasing demands for wireless network bandwidth in recent years. Although evolving transmission techniques are able to enlarge the network capacity to some degree, they still cannot satisfy the requirements of mobile users. Meanwhile, following Moore's Law, the data processing capabilities of mobile user terminals are continuously improving. In this paper, we explore possible methods of trading strong computational power at wireless terminals for transmission efficiency of communications. Taking the specific scenario of wireless video conversation, we propose a model-based video coding scheme by learning the structures in multimedia contents. Benefiting from both strong computing capability and pre-learned model priors, only low-dimensional parameters need to be transmitted; and the intact multimedia contents can also be reconstructed at the receivers in real-time. Experiment results indicate that, compared to conventional video codecs, the proposed scheme significantly reduces the data rate with the aid of computational capability at wireless terminals.展开更多
基金supported by National Natural Science Foundation of China under Grant No.610700800973 Sub-Program Projects under Grant No.2009CB320906+3 种基金National Science and Technology of Major Special Projects under Grant No.2010ZX03004-003S&T Planning Project of Hubei Provincial Department of Education under Grant No. Q20112805H&SPlanning Project of Hubei Provincial Department of Education under Grant No.2011jyte142Science Foundation of HubeiProvincial under Grant No.2010CDB05103
文摘In order to further improve the efficiency of video compression, we introduce a perceptual characteristics of Human Visual System (HVS) to video coding, and propose a novel video coding rate control algorithm based on human visual saliency model in H.264/AVC. Firstly, we modifie Itti's saliency model. Secondly, target bits of each frame are allocated through the correlation of saliency region between the current and previous frame, and the complexity of each MB is modified through the saliency value and its Mean Absolute Difference (MAD) value. Lastly, the algorithm was implemented in JVT JM12.2. Simulation results show that, comparing with traditional rate control algorithm, the proposed one can reduce the coding bit rate and improve the reconstructed video subjective quality, especially for visual saliency region. It is very suitable for wireless video transmission.
基金supported by the National Basic Research Project of China (973) (2013CB329006)National Natural Science Foundation of China (NSFC, 61101071,61471220, 61021001)Tsinghua University Initiative Scientific Research Program
文摘The growing number of mobile users, as well as the diversification in types of services have resulted in increasing demands for wireless network bandwidth in recent years. Although evolving transmission techniques are able to enlarge the network capacity to some degree, they still cannot satisfy the requirements of mobile users. Meanwhile, following Moore's Law, the data processing capabilities of mobile user terminals are continuously improving. In this paper, we explore possible methods of trading strong computational power at wireless terminals for transmission efficiency of communications. Taking the specific scenario of wireless video conversation, we propose a model-based video coding scheme by learning the structures in multimedia contents. Benefiting from both strong computing capability and pre-learned model priors, only low-dimensional parameters need to be transmitted; and the intact multimedia contents can also be reconstructed at the receivers in real-time. Experiment results indicate that, compared to conventional video codecs, the proposed scheme significantly reduces the data rate with the aid of computational capability at wireless terminals.
