scholarly journals Block Compressive Sensing Single-View Video Reconstruction Using Joint Decoding Framework for Low Power Real Time Applications

2020 ◽  
Vol 10 (22) ◽  
pp. 7963
Author(s):  
Mansoor Ebrahim ◽  
Syed Hasan Adil ◽  
Kamran Raza ◽  
Syed Saad Azhar Ali
Keyword(s):  
Compressive Sensing ◽  
Real Time ◽  
Side Information ◽  
Rate Distortion ◽  
Sensor Nodes ◽  
Single View ◽  
Video Codecs ◽  
Joint Decoding ◽  
Key Frames ◽  
Video Reconstruction

Several real-time visual monitoring applications such as surveillance, mental state monitoring, driver drowsiness and patient care, require equipping high-quality cameras with wireless sensors to form visual sensors and this creates an enormous amount of data that has to be managed and transmitted at the sensor node. Moreover, as the sensor nodes are battery-operated, power utilization is one of the key concerns that must be considered. One solution to this issue is to reduce the amount of data that has to be transmitted using specific compression techniques. The conventional compression standards are based on complex encoders (which require high processing power) and simple decoders and thus are not pertinent for battery-operated applications, i.e., VSN (primitive hardware). In contrast, compressive sensing (CS) a distributive source coding mechanism, has transformed the standard coding mechanism and is based on the idea of a simple encoder (i.e., transmitting fewer data-low processing requirements) and a complex decoder and is considered a better option for VSN applications. In this paper, a CS-based joint decoding (JD) framework using frame prediction (using keyframes) and residual reconstruction for single-view video is proposed. The idea is to exploit the redundancies present in the key and non-key frames to produce side information to refine the non-key frames’ quality. The proposed method consists of two main steps: frame prediction and residual reconstruction. The final reconstruction is performed by adding a residual frame with the predicted frame. The proposed scheme was validated on various arrangements. The association among correlated frames and compression performance is also analyzed. Various arrangements of the frames have been studied to select the one that produces better results. The comprehensive experimental analysis proves that the proposed JD method performs notably better than the independent block compressive sensing scheme at different subrates for various video sequences with low, moderate and high motion contents. Also, the proposed scheme outperforms the conventional CS video reconstruction schemes at lower subrates. Further, the proposed scheme was quantized and compared with conventional video codecs (DISCOVER, H-263, H264) at various bitrates to evaluate its efficiency (rate-distortion, encoding, decoding).

Real Time Compressive Sensing Video Reconstruction in Hardware

2012 ◽  
Vol 2 (3) ◽  
pp. 604-615 ◽  
Author(s):  
Garrick Orchard ◽  
Jie Zhang ◽  
Yuanming Suo ◽  
Minh Dao ◽  
Dzung T. Nguyen ◽  
...  
Keyword(s):  
Compressive Sensing ◽  
Real Time ◽  
Video Reconstruction

Residual Reconstruction Algorithm Based on Half-Pixel Multi-Hypothesis Prediction for Distributed Compressive Video Sensing

2018 ◽  
Vol 9 (4) ◽  
pp. 16-33
Author(s):  
Ying Tong ◽  
Rui Chen ◽  
Jie Yang ◽  
Minghu Wu
Keyword(s):  
Side Information ◽  
Sampling Rate ◽  
Reconstruction Algorithm ◽  
Video Frame ◽  
Reconstruction Method ◽  
Reconstruction Algorithms ◽  
Directional Motion ◽  
Key Frames ◽  
Video Reconstruction ◽  
Pixel Interpolation

Compressed sensing (CS) provides a method to sample and reconstruct sparse signals far below the Nyquist sampling rate, which has great potential in image/video acquisition and processing. In order to fully exploit the spatial and temporal characteristics of video frame and the coherence between successive frames, we propose a half-pixel interpolation based residual reconstruction method for distributed compressive video sensing (DCVS). At the decoding end, half-pixel interpolation and bi-directional motion estimation helps refine the side information for joint decoding of the non-key-frames. We apply a multi-hypothesis based on residual reconstruction algorithms to reconstruct the non-key-frames. Performance analysis and simulation experiments show that the quality of side information generated by the proposed algorithm is increased by about 1.5dB, with video reconstruction quality increased 0.3~2dB in PSNR, when compared with prior works on DCVS.

Spatial Interpolators for Intra-Frame Resampling of SAR Videos: A Comparative Study Using Real-Time HD, Medical and Radar Data

2020 ◽  
Vol 15 (2) ◽  
pp. 144-196 ◽  
Author(s):  
Mohammad R. Khosravi ◽  
Sadegh Samadi ◽  
Reza Mohseni
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Video Compression ◽  
Nearest Neighbor ◽  
Radar Data ◽  
Edge Preservation ◽  
Edge Information ◽  
Video Codecs ◽  
Comparative Results ◽  
Interesting Area

Background: Real-time video coding is a very interesting area of research with extensive applications into remote sensing and medical imaging. Many research works and multimedia standards for this purpose have been developed. Some processing ideas in the area are focused on second-step (additional) compression of videos coded by existing standards like MPEG 4.14. Materials and Methods: In this article, an evaluation of some techniques with different complexity orders for video compression problem is performed. All compared techniques are based on interpolation algorithms in spatial domain. In details, the acquired data is according to four different interpolators in terms of computational complexity including fixed weights quartered interpolation (FWQI) technique, Nearest Neighbor (NN), Bi-Linear (BL) and Cubic Cnvolution (CC) interpolators. They are used for the compression of some HD color videos in real-time applications, real frames of video synthetic aperture radar (video SAR or ViSAR) and a high resolution medical sample. Results: Comparative results are also described for three different metrics including two reference- based Quality Assessment (QA) measures and an edge preservation factor to achieve a general perception of various dimensions of the mentioned problem. Conclusion: Comparisons show that there is a decidable trade-off among video codecs in terms of more similarity to a reference, preserving high frequency edge information and having low computational complexity.

scholarly journals A Remote Monitoring System of Logistics Carrier Based on Wireless Sensor Network

2018 ◽  
Vol 14 (01) ◽  
pp. 4
Author(s):  
Wang Weidong
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Monitoring Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Remote Monitoring System ◽  
Monitoring Center

To improve the efficiency of the remote monitoring system for logistics transportation, we proposed a remote monitoring system based on wireless sensor network and GPRS communication. The system can collect information from the wireless sensor network and transmit the information to the ZigBee interpreter. The monitoring system mainly includes the following parts: Car terminal, GPRS transmission network and monitoring center. Car terminal mainly consists by the Zigbee microcontroller and peripherals, wireless sensor nodes, RFID reader, GPRS wireless communication module composed of a micro-wireless monitoring network. The information collected by the sensor communicates through the GPRS and the monitoring center on the network coordinator, sends the collected information to the monitoring center, and the monitoring center realizes the information of the logistics vehicle in real time. The system has high applicability, meets the design requirements in the real-time acquisition and information transmission of the information of the logistics transport vehicles and goods, and realizes the function of remote monitoring.

scholarly journals Calculating the Number of Cluster Heads Based on the Rate-Distortion Function in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Mingxin Yang ◽  
Jingsha He ◽  
Yuqiang Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Rate Distortion ◽  
Distortion Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Cluster Heads

Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs). Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

scholarly journals Comparative Rate-Distortion-Complexity Analysis of HEVC and AVC Video Codecs

2012 ◽  
Vol 22 (12) ◽  
pp. 1885-1898 ◽  
Author(s):  
Jarno Vanne ◽  
Marko Viitanen ◽  
Timo D. Hamalainen ◽  
Antti Hallapuro
Keyword(s):  
Complexity Analysis ◽  
Rate Distortion ◽  
Video Codecs ◽  
Comparative Rate

scholarly journals Comparative Rate-Distortion-Complexity Analysis of VVC and HEVC Video Codecs

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Alexandre Mercat ◽  
Arttu Makinen ◽  
Joose Sainio ◽  
Ari Lemmetti ◽  
Marko Viitanen ◽  
...  
Keyword(s):  
Complexity Analysis ◽  
Rate Distortion ◽  
Video Codecs ◽  
Comparative Rate

Dynamic Resource Allocation for Compressive-Sensing-Based Wireless Visual Sensor Networks with Energy Harvesting

2013 ◽  
Vol 303-306 ◽  
pp. 187-190
Author(s):  
Lei You ◽  
Xin Su ◽  
Yu Tong Han
Keyword(s):  
Resource Allocation ◽  
Energy Harvesting ◽  
Compressive Sensing ◽  
Information Acquisition ◽  
Visual Information ◽  
Sensor Nodes ◽  
Visual Sensor ◽  
Visual Sensor Network ◽  
Available Bandwidth ◽  
Potential Applications

Wireless visual sensor network (WVSN) is emerging with many potential applications. The lifetime of a WVSN is seriously dependent on the energy shored in the battery of its sensor nodes as well as the adopted compression and resource allocation scheme. In this paper, we use the energy harvesting to provide almost perpetual operation of the networks and compressed-sensing-based encoding to decrease the power consumption of acquiring visual information at the front-end sensors. We propose a dynamic algorithm to jointly allocate power for both compressive-sensing-based visual information acquisition and data transmission, as well as the available bandwidth under energy harvesting and stability constraints. A virtual energy queue is introduced to control the resource allocation and the measurement rate in each time slot. The algorithm can guarantee the stability of the visual data queues in all sensors and achieve near-optimal performance.

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