Low-overhead video compression combining partial discrete cosine transform and compressed sensing in WMSNs

Banerjee, Rajib; Bit, Sipra Das

doi:10.1007/s11276-019-02119-y

Cited by 14 publications

(8 citation statements)

References 38 publications

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“…To find the energy consumption by the nodes in the network operation, the widely adopted first-order radio model [13,28,42,[46][47][48][49][50][51][52] has been used here in this work.…”

Section: Simulation Parametersmentioning

confidence: 99%

Metaheuristic Load-Balancing-Based Clustering Technique in Wireless Sensor Networks

Chaurasiya

Biswas

Bandyopadhyay

et al. 2022

Wireless Communications and Mobile Computing

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The resource-constrained nature of wireless sensor networks engenders the development of energy-efficient network operations. To mitigate the prime concern of developing an energy-efficient network, clustering of the nodes has emerged as a very effective tool. If executed intelligently, clustering can not only help in obtaining even load distribution among the network nodes but also help in having the enhanced network lifetime and scalability. In this work, a Metaheuristic Load-Balancing-Based Clustering Technique (MLBCT) in wireless sensor networks has been proposed which formulates the energy-balanced clusters based on the differential evolution technique to improve the network lifetime. To ensure the formation of balanced clusters, several metrics like nodes’ proximity, nodes’ distribution, and energy distribution across the sensing field have been considered. Moreover, to facilitate the even load distribution among the cluster members, a randomized rotation of cluster head is implemented. The supremacy of the proposed scheme is confirmed through an extensive set of simulations against the state-of-art schemes. Simulation results reflect an average gain of 51.85% in network lifetime under the variable network configurations in an ideal environment. Moreover, a thorough statistical analysis is performed to prove the efficacy of the proposed fitness function by obtaining confidence intervals under two different network scenarios with variable node counts.

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“…To find the energy consumption by the nodes in the network operation, the widely adopted first-order radio model [13,28,42,[46][47][48][49][50][51][52] has been used here in this work.…”

Section: Simulation Parametersmentioning

confidence: 99%

Metaheuristic Load-Balancing-Based Clustering Technique in Wireless Sensor Networks

Chaurasiya

Biswas

Bandyopadhyay

et al. 2022

Wireless Communications and Mobile Computing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Resultant quantized factors are then traversed in crisscrossed fashionaiming to fragment the coefficients of DCT using macro chunk level dissection into two fold sub streams. Fragmentation of video into frames is done whenever it is sensed by a node [33]. Here every frame in RGB color domain are converted into luminance-chrominance (YCbCr) color domain so as to eliminate the RGB color space redundant components which are storage incompetent and not transmission efficient.…”

Section: Transformationmentioning

confidence: 99%

“…Thus considering constraints, researchers are motivated to design an enhanced encoding methods. When there is a proliferation in quantized bit stream size in the process of encoding [33], then there is a reduction in average number of bits to be trimmed which in turn obstructs the efficiency of transmission. Therefore in order to increase the average truncation bits count during encoding, those quantized stream of bits can be partitioned as either into two or three or many parts.…”

Section: Entropy Encodingmentioning

confidence: 99%

State-Of-The-Art In Video Processing: Compression, Optimization And Retrieval

Megala¹

2021

TURCOMAT

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Video compression plays a vital role in the modern social media networking with plethora of multimedia applications. It empowers transmission medium to competently transfer videos and enable resources to store the video efficiently. Nowadays high-resolution video data are transferred through the communication channel having high bit rate in order to send multiple compressed videos. There are many advances in transmission ability, efficient storage ways of these compressed video where compression is the primary task involved in multimedia services. This paper summarizes the compression standards, describes the main concepts involved in video coding. Video compression performs conversion of large raw bits of video sequence into a small compact one, achieving high compression ratio with good video perceptual quality. Removing redundant information is the main task in the video sequence compression. A survey on various block matching algorithms, quantization and entropy coding are focused. It is found that many of the methods having computational complexities needs improvement with optimization.

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“…This work aims to investigate the development of moving object detection over WVSN. The Discrete Cosine Transform (DCT) [14] is a frequently utilised image compression technique over WVSN [15,16]. The DCT algorithm converts signals from the spatial domain to a frequency domain representation.…”

Section: Introductionmentioning

confidence: 99%

Moving Object Detection over Wireless Visual Sensor Networks using Spectral Dual Mode Background Subtraction

AbdelTawab¹,

Abdelhalim²,

Habib³

2022

IJACSA

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Wireless Visual Sensor Networks (WVSN) play an essential role in tracking moving objects. WVSN's key drawbacks are storage, power, and bandwidth. Background subtraction is used in the early stages of target tracking to extract moving targets from video images. Many standard methods of subtracting backgrounds are no longer suitable for embedded devices because they use complex statistical models to manage small changes in lighting. This paper introduces a system based on the Partial Discrete Cosine Transform (PDCT), reducing the vast dimensions of processed data while retaining most of the important information, thereby reducing processing and transmission energy. It also uses a dual-mode single Gaussian model (SGM) for accurate detection of moving objects. The proposed system's performance is to be assessed using the standard CDnet 2014 benchmark dataset in terms of detection accuracy and time complexity. Furthermore, the suggested method is compared to previous WVSN background subtraction methods. Simulation results show that the proposed method consistently has 15% better accuracy and is up to 3 times faster than the state-of-the-art object detection methods for WVSN. Finally, we showed the practicality of the suggested method by simulating it in a sensor network environment using the Contiki OS Cooja Simulator and implementing it in a real testbed using Cortex M3 open nodes of IOT-LAB.

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Low-overhead video compression combining partial discrete cosine transform and compressed sensing in WMSNs

Cited by 14 publications

References 38 publications

Metaheuristic Load-Balancing-Based Clustering Technique in Wireless Sensor Networks

Metaheuristic Load-Balancing-Based Clustering Technique in Wireless Sensor Networks

State-Of-The-Art In Video Processing: Compression, Optimization And Retrieval

Moving Object Detection over Wireless Visual Sensor Networks using Spectral Dual Mode Background Subtraction

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