4666459
Synchronous and asynchronous multiple object rate control for MPEG-4 video coding
Video scenes containing multiple objects can potentially achieve higher degree of compression and better visual quality with individual coding for each object. Video objects are not always synchronous, implying each object may have a separate temporal resolution. This paper proposes a rate control algorithm for multiple video object encoding. Using a novel bit allocation strategy, the algorithm achieves accurate target bit rate, provides good visual quality, and decreases buffer overflow/underflow. Experimental results for both synchronous and asynchronous multiple video object encoding demonstrate that, when compared with the existing rate control scheme recommended by the MPEG-4 standard, the proposed algorithm provide better temporal-spatial tradeoff with more accurate rate regulation.
8440598
A rate control algorithm for wireless video transmission using perceptual tuning
In video transmission over two-way wireless channel automatic repeat request (ARQ) retransmission has been used to protect packets from losing, which also causes the channel throughput varying and brings more challenges to rate control of the video compression. This paper proposes a new rate control algorithm based on regions of interest (ROI), PID buffer controlling and perceptual tuning techniques, etc. It intelligently allocates bit budget among different regions and adapts to time-varying wireless channel so as to achieve better perceptual quality in ROI and depress the frame skipping. Simulation results illustrate that our algorithm effectively enhances the perceptual quality for ROI, significantly reduces the number of frame skipping, and thereby improves the smoothness of the video.
9615760
Asynchronous rate control for multi-object videos
Object-based coding can potentially achieve a higher degree of compression and better visual quality. The objects in a scene are not always synchronous, that is, they have different temporal resolutions. In some applications, it is more efficient to transmit asynchronous objects with different temporal rates so as to achieve a better tradeoff between temporal and spatial resolutions. This requires to balance the qualities of individual objects while ensuring an overall visual quality with a given bit rate. This paper proposes a rate control algorithm for multiple video object encoding, which is suitable for both synchronous and asynchronous transmissions. The algorithm aims to maximize scene quality with an accurate bit rate, while efficiently handling buffer fullness. Using an efficient bit allocation strategy, the algorithm achieves accurate target bit rates, provides good coding quality, and decreases buffer overflow/underflow. The proposed algorithm also allows flexible priority adjustment among multiple objects to ensure overall better visual perception. Designed primarily for asynchronous objects, the algorithm treats the synchronous objects as a special case. Experimental results demonstrate that, when giving suitable asynchronous video object planes rates, the proposed algorithm achieves good temporal-spatial tradeoff while yielding accurate rate regulation and effective buffer control.
16523105
Region-based rate control and bit allocation for wireless video transmission
In this paper, we propose a joint source-channel region-based rate control algorithm for real-time video transmissions over wireless systems. During the video transmission, the channel throughput available to the video encoder in the wireless systems is inherently variable, due to the retransmission of the error packets using the automatic repeat request (ARQ) error control. The variable data rate of the wireless system is characterized by the packet-level Gilbert two-state Markov Model, the parameters of which are extracted from the statistical properties of the channel information obtained from the wireless channel simulator. The proposed algorithm adopts a fast but effective block-based segmentation method to extract the regions of interest. Unlike traditional bit allocation methods used in the region/content-based rate control, the algorithm exploits the most effective criteria "coding qualities" as quantitative factors to directly control bit allocation among different regions so as to achieve better visual quality in the regions of interest. The computational complexity of the algorithm is low making it suitable for real-time applications. Compared with the MPEG-4 rate control algorithm, our algorithm can effectively enhance the perceptual quality for the regions of interest and significantly reduce the number of frame skipping; thereby, improve the smoothness of the video.
47269670
Motion estimation for content adaptive video compression
A multistage motion estimation scheme is proposed. The scheme extracts video characteristics by first performing an online video analysis separately for foreground and background regions. Motion parameters are extracted and passed to the next stage. The next stage includes a mathematical model for the block distortion surface (BDS) that enables the algorithm to accordingly adjust its search technique. The search is performed on a precise search area adaptive to the statistical property of the motion vector prediction error. Due to its self-tuning property, not only does the proposed scheme adapt to scenes by yielding better visual quality but it also yields a lower computational complexity, compared with the other predictive motion estimation algorithms on standard benchmark sequences
28447870
On quantization error of self-organizing map network
Abstract In this paper, we analyze how neighborhood size and number of weights in the self-organizing map (SOM) effect quantization error. A sequence of i.i.d. one-dimensional random variable with uniform distribution is considered as input of the SOM. First obtained is the linear equation that an equilibrium state of the SOM satisfies with any neighborhood size and number of weights. Then it is shown that the SOM converges to the unique minimum point of quantization error if and only if the neighborhood size is one, the smallest. If the neighborhood size increases with the increasing number of weights at the same ratio, the asymptotic quantization error does not converge to zero and the asymptotic distribution of weights differs from the distribution of input samples. This suggests that in order to achieve a small quantization error and good approximation of input distribution, a small neighborhood size must be used. Weight distributions in numerical evaluation confirm the result.
3124333
Stochastic iterative algorithms for signal set design for Gaussian channels and optimality of the L2 signal set
We propose a stochastic iteration approach to signal set design. Four practical stochastic iterative algorithms are proposed with respect to equal and average energy constraints and sequential and batch modes. By simulation, a new optimal signal set, the L2 signal set (consisting of a regular simplex set of three signals and some zero signals), is found under the strong simplex conjecture (SSC) condition (equal a priori probability and average energy constraint) at low signal-to-noise ratios (SNR). The optimality of the L1 signal set, the confirmation of the weak simplex conjecture, and two of Dunbridge's (1967) theorems are some of the results obtained by simulations. The influence of SNR and a priori probabilities on the signal sets is also investigated via simulation. As an application to practical communication system design, the signal sets of eight two-dimensional (2-D) signals are studied by simulation under the SSC condition. Two signal sets better than 8-PSK are found. Optimal properties of the L2 signal set are analyzed under the SSC condition at low SNRs. The L2 signal set is proved to be uniquely optimal in 2-D space. The class of signal sets S(M, K) (consisting of a regular simplex set of K signals and M-K zero signals) is analyzed. It is shown that any of the signal sets S(M, K) for 3/spl les/K/spl les/M-1 disproves the strong simplex conjecture for M/spl ges/4, and if M/spl ges/7, S(M, 2) (the L1 signal set) also disproves the strong simplex conjecture. It is proved that the L2 signal set is the unique optimal signal set in the class of signal sets S(M, K) for all M/spl ges/4. Several results obtained by Steiner (see ibid., vol.40, no.5, p.721-31, 1994) for all M/spl ges/7 are extended to all M/spl ges/4. Finally, we show that for M/spl ges/7, there exists an integer K'
12751111
A taxonomy of application scheduling tools for high performance cluster computing
Application scheduling plays an important role in high-performance cluster computing. Application scheduling can be classified as job scheduling and task scheduling. This paper presents a survey on the software tools for the graph-based scheduling on cluster systems with the focus on task scheduling. The tasks of a parallel or distributed application can be properly scheduled onto multi-processors in order to optimize the performance of the program (e.g., execution time or resource utilization). In general, scheduling algorithms are designed based on the notion of task graph that represents the relationship of parallel tasks. The scheduling algorithms map the nodes of a graph to the processors in order to minimize overall execution time. Although many scheduling algorithms have been proposed in the literature, surprisingly not many practical tools can be found in practical use. After discussing the fundamental scheduling techniques, we propose a framework and taxonomy for the scheduling tools on clusters. Using this framework, the features of existing scheduling tools are analyzed and compared. We also discuss the important issues in improving the usability of the scheduling tools.
12119839
Performance analysis of maximum intensity projection algorithm for display of MRA images
The maximum intensity projection (MIP) is a popularly used algorithm for display of MRA images, but its performance has not been rigorously analyzed before. In this paper, four measures are proposed for the performance of the MIP algorithm and the quality of images projected from three-dimensional (3-D) data, which are vessel voxel projection probability, vessel detection probability, false vessel probability, and vessel-tissue contrast-to-noise ratio (CNR). As side products, vessel-missing probability, vessel receiver operating characteristics (ROC's), and mean number of false vessels are also studied. Based on the assumptions that the intensities of vessel, tissue, and noise along a projection path are independent Gaussian, these measures are derived and obtained all in closed forms. All the measures are functions of explicit parameters: vessel-to-tissue noise ratio (VTNR) and CNR of 3 D data prior to the MIP, vessel diameter, and projection length. It is shown that the MIP algorithm increases the CNR of large vessels whose CNR prior to the MIP is high and whose diameters are large. The increase in CNR increases with projection path length. On the other hand, all the proposed measures indicate that the small vessels that have low CNR prior to the MIP and small diameters suffer from the MIP. The performance gets worse as projection path length increases. All measures demonstrate a better performance when the vessel diameter is larger. Other properties and possible applications of the derived measures are also discussed.
205906582
Polygonal approximation using genetic algorithms
A polygon approximation method based on genetic algorithms is proposed in this paper. In the method, a chromosome is used to represent a polygon and is represented by a binary string. Each bit, called a gene, represents a point on the object curve. The objective function is defined as the integral square error between the given curve and the approximated polygon. Three genetic operators namely selection, crossover and mutation, have been constructed for this specific problem. The proposed method when compared with three existing methods can obtain superior approximation results with less error norm with respect to the original curves.