Frame skipping in low bit video coding could significantly reduce the visual quality of reconstructed video. At the same time, if the complexity of the video sequence remains high for a long period, then driving up th...Frame skipping in low bit video coding could significantly reduce the visual quality of reconstructed video. At the same time, if the complexity of the video sequence remains high for a long period, then driving up the long term average bit rate, the only resort of MPEG-4 Q2 rate control algorithm results in using a high quantization scale, which shows a poor visual quality of the reconstructed video. This paper analyzes the main causes of frame skipping in current MPEG-4 frame rate control scheme, and presents a new rate control algorithm based on the quadratic R-D model over a CBR channel. Key features of the present work are: 1) the bits allocated to each P-frame or B-frame are in proportion to its distance from the end of this GOP, i.e. more bits are allocated to the frames that are nearer to their reference Ⅰ-frame; 2) the target buffer level is changeable in the GOP, at the end of each GOP(five P-frames or B-frames), the target buffer level is linearly reduced from 1/2 to 1/4 of buffer size, to other frames, the target buffer level is set to 1/2 of buffer size; 3) a selective and judicious use of the reduced resolution mode, in addition to a modulation of the quantization scale parameter, is to control the average long term bit rate. Experimental results with different video sequences of varied complexity, encoded at low bit rates show better efficacy of the proposed algorithm than MPEG-4 Q2 rate control scheme, and the experimental results also show that the improved algorithm has significantly reduced the number of frame skipping, increased the overall PSNR, and improved the perceptual quality.展开更多
For sparse coding, the weaker the correlation of dictionary atoms is, the better the representation capacity of dictionary will be. A weak correlation dictionary construction method for sparse coding has been proposed...For sparse coding, the weaker the correlation of dictionary atoms is, the better the representation capacity of dictionary will be. A weak correlation dictionary construction method for sparse coding has been proposed in this paper. Firstly, a new dictionary atom initialization is proposed in which data samples with weak correlation are selected as the initial dictionary atoms in order to effectively reduce the correlation among them.Then, in the process of dictionary learning, the correlation between atoms has been measured by correlation coefficient, and strong correlation atoms have been eliminated and replaced by weak correlation atoms in order to improve the representation capacity of the dictionary. An image classification scheme has been achieved by applying the weak correlation dictionary construction method proposed in this paper. Experimental results show that, the proposed method averagely improves image classification accuracy by more than 2%, compared to sparse coding spatial pyramid matching(Sc SPM) and other existing methods for image classification on the datasets of Caltech-101, Scene-15, etc.展开更多
文摘Frame skipping in low bit video coding could significantly reduce the visual quality of reconstructed video. At the same time, if the complexity of the video sequence remains high for a long period, then driving up the long term average bit rate, the only resort of MPEG-4 Q2 rate control algorithm results in using a high quantization scale, which shows a poor visual quality of the reconstructed video. This paper analyzes the main causes of frame skipping in current MPEG-4 frame rate control scheme, and presents a new rate control algorithm based on the quadratic R-D model over a CBR channel. Key features of the present work are: 1) the bits allocated to each P-frame or B-frame are in proportion to its distance from the end of this GOP, i.e. more bits are allocated to the frames that are nearer to their reference Ⅰ-frame; 2) the target buffer level is changeable in the GOP, at the end of each GOP(five P-frames or B-frames), the target buffer level is linearly reduced from 1/2 to 1/4 of buffer size, to other frames, the target buffer level is set to 1/2 of buffer size; 3) a selective and judicious use of the reduced resolution mode, in addition to a modulation of the quantization scale parameter, is to control the average long term bit rate. Experimental results with different video sequences of varied complexity, encoded at low bit rates show better efficacy of the proposed algorithm than MPEG-4 Q2 rate control scheme, and the experimental results also show that the improved algorithm has significantly reduced the number of frame skipping, increased the overall PSNR, and improved the perceptual quality.
基金the National Natural Science Foundation of China(Nos.61372149,61370189,and 61471013)the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions(Nos.CIT&TCD20150311,CIT&TCD201304036,and CIT&TCD201404043)+3 种基金the Program for New Century Excellent Talents in University of China(No.NCET-11-0892)the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20121103110017)the Natural Science Foundation of Beijing(No.4142009)the Science and Technology Development Program of Beijing Education Committee(No.KM201410005002)
文摘For sparse coding, the weaker the correlation of dictionary atoms is, the better the representation capacity of dictionary will be. A weak correlation dictionary construction method for sparse coding has been proposed in this paper. Firstly, a new dictionary atom initialization is proposed in which data samples with weak correlation are selected as the initial dictionary atoms in order to effectively reduce the correlation among them.Then, in the process of dictionary learning, the correlation between atoms has been measured by correlation coefficient, and strong correlation atoms have been eliminated and replaced by weak correlation atoms in order to improve the representation capacity of the dictionary. An image classification scheme has been achieved by applying the weak correlation dictionary construction method proposed in this paper. Experimental results show that, the proposed method averagely improves image classification accuracy by more than 2%, compared to sparse coding spatial pyramid matching(Sc SPM) and other existing methods for image classification on the datasets of Caltech-101, Scene-15, etc.
