scholarly journals Virtual Viewpoint Film and Television Synthesis Based on the Intelligent Algorithm of Wireless Network Communication for Image Repair

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Jianfeng Zhang
Keyword(s):  
Computer Vision ◽  
Wireless Sensor Network ◽  
Swarm Intelligence ◽  
Sensor Network ◽  
Wireless Network ◽  
Wireless Sensor ◽  
Intelligent Algorithm ◽  
Intelligence Algorithm ◽  
Traditional Algorithm ◽  
Swarm Intelligence Algorithm

With the development of the computer vision field, the acquisition of scene depth information is one of the important topics in the three-dimensional reconstruction of the computer vision field, and its significance is particularly important. The purpose of this paper is to study the virtual viewpoint video synthesis for image restoration based on the intelligent algorithm of wireless network communication. Aiming at the hole problem caused by the change of occlusion relationship, this paper proposes a hole-filling method based on background recognition. A threshold segmentation algorithm is used to reduce the filling priority of foreground pixels at the boundary of the hole and fully solve the hole problem. This paper also proposes a wireless sensor network node positioning model with swarm intelligence algorithm, which combines swarm intelligence algorithm with some key issues of wireless sensor network, speeds up the convergence, and improves the traditional intelligence algorithm. According to the experimental data in this paper, the algorithm in this paper is about 20% higher than the traditional algorithm in PSNR. On SSIM, the performance of the algorithm in this paper is 4.6% higher than the traditional algorithm at most, and the lowest is 2.2%.

scholarly journals Coverage Optimization Strategy for WSN based on Energy-aware

2016 ◽  
Vol 11 (6) ◽  
pp. 877 ◽  
Author(s):  
Li Zhu ◽  
Chunxiao Fan ◽  
Zhigang Wen ◽  
Huarun Wu
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Path Loss ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimization Strategy ◽  
Network Coverage ◽  
Energy Aware ◽  
Coverage Optimization

In order to optimize the wireless sensor network coverage, this paper designs a coverage optimization strategy for wireless sensor network (EACS) based on energy-aware. Under the assumption that the geographic positions of sensor nodes are available, the proposed strategy consists of energy-aware and network coverage adjustment. It is restricted to conditions such as path loss, residual capacity and monitored area and according to awareness ability of sensors, it would adjust the monitored area, repair network hole and kick out the redundant coverage. The purpose is to balance the energy distribution of working nodes, reduce the number of “dead” nodes and balance network energy consumption. As a result, the network lifetime is expanded. Simulation results show that: EACS effectively reduces the number of working nodes, improves network coverage, lowers network energy consumption while ensuring the wireless sensor network coverage and connectivity, so as to balance network energy consumption.

scholarly journals Novel Bacteria Foraging Optimization for Energy-efficient Communication in Wireless Sensor Network

2018 ◽  
Vol 8 (6) ◽  
pp. 4755
Author(s):  
Hemavathi P ◽  
Nandakumar A. N.
Keyword(s):  
Wireless Sensor Network ◽  
Swarm Intelligence ◽  
Sensor Network ◽  
Energy Efficient ◽  
Residual Energy ◽  
Optimization Techniques ◽  
Wireless Sensor ◽  
Efficient Communication ◽  
Communication Demands ◽  
Standard Energy

Optimization techniques based on Swarm-intelligence has been reported to have significant benefits towards addressing communication issues in Wireless Sensor Network (WSN). We reviewed the most dominant swarm intelligence technique called as Bacteria Foraging Optimization (BFO) to find that there are very less significant model towards addressing the problems in WSN. Therefore, the proposed paper introduced a novel BFO algorithm which maintains a very good balance between the computational and communication demands of a sensor node unlike the conventional BFO algorithms. The significant contribution of the proposed study is to minimize the iterative steps and inclusion of minimization of both receiving / transmittance power in entire data aggregation process. The study outcome when compared with standard energy-efficient algorithm was found to offer superior network lifetime in terms of higher residual energy as well as data transmission performance.

Sign in / Sign up

Export Citation Format

Share Document