scholarly journals Fast Motion Estimation’s Configuration Using Diamond Pattern and ECU, CFM, and ESD Modes for Reducing HEVC Computational Complexity

2020 ◽  
Author(s):  
Randa Khemiri ◽  
Nejmeddine Bahri ◽  
Fatma Belghith ◽  
Soulef Bouaafia ◽  
Fatma Elzahra Sayadi ◽  
...  
Keyword(s):  
Computational Complexity ◽  
Fast Motion

scholarly journals A Dynamic Predictive Search Algorithm for Fast Block-Based Motion Estimation

2021 ◽  
Author(s):  
Behnaz Abdoli
Keyword(s):  
Computational Complexity ◽  
Motion Estimation ◽  
Compression Ratio ◽  
Video Processing ◽  
Search Algorithm ◽  
Fast Motion Estimation ◽  
Low Computational Complexity ◽  
Video Codecs ◽  
Fast Motion ◽  
Block Based

Predictive fast Motion Estimation (ME) algorithms have been widely used in video CODECs due to their performance efficiency and low computational complexity. In this thesis, a new block-based fast motion estimation technique named Dynamic Predictive Search Algorithm (DPSA) is developed, which can be considered in predictive zonal search category. The proposed approach is based on the observation that temporally and spatially adjacent macro-blocks are not just statically correlated, but also dynamic alterations in their motion content are highly coherent. DPSA introduces a new set of six candidate predicted motion vectors. For early termination criteria, DPSA modifies termination procedure of already existing EPZS algorithm. Performance of this newly proposed algorithm has been compared to four other state-of-the-art algorithms implemented on JVT, H.264 standard software platform. Experimental results have proven that DPSA accomplishes up to 38% compression ratio enhancement achieved by a process with more 14.75% less computational complexity and up to0.47 dB higher PSNR values over the EPZS. It also manages to have up to 13% speed up over EPZS algorithm. Because of its simplicity and low computational complexity DPSA is energy efficient for portable video processing in computation- or power-constrained applications and easy to be implemented on both FPGA- and Microcontroller-based embedded systems. Also, higher compression ratio makes DPSA more compatible with limited capacity storage media, and limited band-width transmission networks.

scholarly journals A Dynamic Predictive Search Algorithm for Fast Block-Based Motion Estimation

2021 ◽  
Author(s):  
Behnaz Abdoli
Keyword(s):  
Computational Complexity ◽  
Motion Estimation ◽  
Compression Ratio ◽  
Video Processing ◽  
Search Algorithm ◽  
Fast Motion Estimation ◽  
Low Computational Complexity ◽  
Video Codecs ◽  
Fast Motion ◽  
Block Based

Predictive fast Motion Estimation (ME) algorithms have been widely used in video CODECs due to their performance efficiency and low computational complexity. In this thesis, a new block-based fast motion estimation technique named Dynamic Predictive Search Algorithm (DPSA) is developed, which can be considered in predictive zonal search category. The proposed approach is based on the observation that temporally and spatially adjacent macro-blocks are not just statically correlated, but also dynamic alterations in their motion content are highly coherent. DPSA introduces a new set of six candidate predicted motion vectors. For early termination criteria, DPSA modifies termination procedure of already existing EPZS algorithm. Performance of this newly proposed algorithm has been compared to four other state-of-the-art algorithms implemented on JVT, H.264 standard software platform. Experimental results have proven that DPSA accomplishes up to 38% compression ratio enhancement achieved by a process with more 14.75% less computational complexity and up to0.47 dB higher PSNR values over the EPZS. It also manages to have up to 13% speed up over EPZS algorithm. Because of its simplicity and low computational complexity DPSA is energy efficient for portable video processing in computation- or power-constrained applications and easy to be implemented on both FPGA- and Microcontroller-based embedded systems. Also, higher compression ratio makes DPSA more compatible with limited capacity storage media, and limited band-width transmission networks.

Bipolar Abstract Argumentation with Dual Attacks and Supports

2020 ◽  
Author(s):  
Nico Potyka
Keyword(s):  
Computational Complexity ◽  
Decision Problems ◽  
Abstract Argumentation ◽  
Stable Semantics ◽  
Support Relations ◽  
Support Relationships ◽  
Computational Properties ◽  
Inherent Tendency

Bipolar abstract argumentation frameworks allow modeling decision problems by defining pro and contra arguments and their relationships. In some popular bipolar frameworks, there is an inherent tendency to favor either attack or support relationships. However, for some applications, it seems sensible to treat attack and support equally. Roughly speaking, turning an attack edge into a support edge, should just invert its meaning. We look at a recently introduced bipolar argumentation semantics and two novel alternatives and discuss their semantical and computational properties. Interestingly, the two novel semantics correspond to stable semantics if no support relations are present and maintain the computational complexity of stable semantics in general bipolar frameworks.

Capacity Analysis for Correlated Multi-Hop MIMO Channels under Colored Noise

2015 ◽  
Vol 1 ◽  
pp. 41
Author(s):  
Nguyen N. Tran ◽  
Ha X. Nguyen
Keyword(s):  
Computational Complexity ◽  
Mutual Information ◽  
Closed Form Solution ◽  
Optimal Solution ◽  
Form Solution ◽  
Maximization Problem ◽  
Capacity Analysis ◽  
Mimo Channels ◽  
Average Mutual Information ◽  
Channel Output

A capacity analysis for generally correlated wireless multi-hop multi-input multi-output (MIMO) channels is presented in this paper. The channel at each hop is spatially correlated, the source symbols are mutually correlated, and the additive Gaussian noises are colored. First, by invoking Karush-Kuhn-Tucker condition for the optimality of convex programming, we derive the optimal source symbol covariance for the maximum mutual information between the channel input and the channel output when having the full knowledge of channel at the transmitter. Secondly, we formulate the average mutual information maximization problem when having only the channel statistics at the transmitter. Since this problem is almost impossible to be solved analytically, the numerical interior-point-method is employed to obtain the optimal solution. Furthermore, to reduce the computational complexity, an asymptotic closed-form solution is derived by maximizing an upper bound of the objective function. Simulation results show that the average mutual information obtained by the asymptotic design is very closed to that obtained by the optimal design, while saving a huge computational complexity.

Fat Computational Complexity and Heuristic Design for the TSP

2009 ◽  
Vol 20 (9) ◽  
pp. 2344-2351 ◽  
Author(s):  
He JIANG ◽  
Yan HU ◽  
Qiang LI ◽  
Hong YU
Keyword(s):  
Computational Complexity
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