Pruned discrete Tchebichef transform for image coding in wireless multimedia sensor networks

Kouadria, Nasreddine; Mechouek, Khaoula; Messadeg, Djemil; Doghmane, Noureddine

doi:10.1016/j.aeue.2017.02.005

Cited by 19 publications

(7 citation statements)

References 17 publications

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“…Several image compression (IC) techniques exist in literature and their choice depends on the type of operating platform. Image compression minimizes redundancies and irrelevant image data for efficient storage and transmission [15] while preserving the visual quality of the reconstructed image [16]. Generally, image compression is done to save storage space and lower bandwidth without compromising the output image quality [16].…”

Section: Figurementioning

confidence: 99%

Image Compression Techniques in Wireless Sensor Networks: A Survey and Comparison

et al. 2022

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There is continuous intensive research on image compression techniques in wireless sensor networks (WSNs) in the literature. Some of the image compression techniques in WSNs that exist in the literature include discrete cosine transform (DCT), discrete waveform transforms (DWT), set partitioning in a hierarchical tree (SPIHT), and embedded zero tree wavelet (EZW) coding. Research on image compression in WSNs is necessitated by the need to improve the energy efficiency of sensor nodes and WSNs' lifetimes without compromising the quality of the reconstructed data. Several approaches have been developed centered around image compression and other factors in trying to limit the energy consumption of sensor nodes. Most of these approaches do not provide the error-bound mechanism that balances the rate of compression and distortion of the reconstructed image. Therefore, in this paper, a review and analysis of image compression techniques and approaches in WSNs are conducted. Available image compression approaches in WSNs in literature were then classified according to the image compression technique adopted, and their strengths and weaknesses were highlighted. In addition, a rate-distortion balanced data compression algorithm with error bound mechanism based on artificial neural networks (ANN) in the form of an autoencoder (AE) was coded and simulated in MATLAB before being evaluated and compared to the conventional approaches. The experimental results show that the simulated algorithm has less root mean square error (RMSE) and a higher coefficient of determination (𝑅 2 ) values on variable compression ratios as compared to the Principal Component Analysis (PCA), Discrete Cosine Transform, and Fast Fourier Transform (FFT) when using the Grand-St-Bernard metrological dataset. Furthermore, it presented less RMSE, and higher compression ratio values compared to the Lightweight Temporal Compression (LTC) algorithm on variable error bounds when using the LUCE metrological dataset. Therefore, it was found that the simulated algorithm presents better compression fidelity as compared to the conventional approaches without an error-bound mechanism. Moreover, the algorithm analyzed presents a significant approach to balancing the compression ratio and reconstructed data quality through its error-bound mechanism.

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Section: Figurementioning

confidence: 99%

Image Compression Techniques in Wireless Sensor Networks: A Survey and Comparison

et al. 2022

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“…In the forwarding network, the future self-organizing anonymity of cities and counties can generate the anonymity of the senders of cities and counties with multiple virtual source nodes through the use of pseudonym strategy; the anonymity of the receiver can be realized by broadcasting information from the exit node to the target node; the anonymity of communication relationship between them can be realized through anonymous relay and forwarding network, In each hop of the forwarding network, a group of nodes is included. Each group of nodes can only understand the specific information of the group nodes of the previous and next hop, and can communicate between the group nodes, thus realizing the anonymity of the communication relationship [16,17]. Figure 1 shows the process of constructing forwarding network and the related anonymity strategy.…”

Section: Correctness Analysis Of Communication Modelmentioning

confidence: 99%

Multimedia Independent Multipath Routing Algorithms for Internet of Things Based on a Node Hidden Communication Model

Jian-hui

2019

Future Internet

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In order to achieve a multi-path routing algorithm with time delay and energy consumption balance to alleviate the energy holes around a sink, a multimedia independent multipath routing algorithm for internet of things (IoT) based on node hidden communication model is proposed in this paper. On the premise of satisfying the application delay, a multi-source multi-path routing algorithm is proposed by using the idea of software definition and fitting multiple curves to form independent multi-path routing. Through a sink node centralized programming control source node routing, according to the priority of the source node, the dynamic angle of the source node can be allocated, which effectively reduces the energy consumption of the network. In addition, considering that the Internet of Things has more perceptive nodes, limited computing and storage capacity, frequent joining and exiting operations and other factors, a hidden communication model of nodes is designed for the IoT. It is helpful to improve the level of privacy protection in the IoT, and to effectively improve the ability of nodes to resist attacks in the IoT. The experimental results show that the proposed algorithm avoids the interference between paths and various network attacks to the greatest extent, and the energy consumption is relatively low under the requirement of quality of service (QoS) delay.

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“…The wireless sensor network has become a predominant technology in the modern technological era, used for monitoring and measuring multiple factors in variety of applications. The wireless sensor nodes not only measure and communicate the primary data but also are significant to communicate the data inclusive of image, 1 video, and other format multimedia files. The purpose of communicating the multimedia files ranges from remote sensing, health care applications, military applications, atmospheric condition monitoring, and so on.…”

Section: Introductionmentioning

confidence: 99%

Design of optimized compressed sensing routing protocol for wireless multimedia sensor networks

Ramesh¹,

Yaashuwanth²,

Prathibanandhi

2021

Int J Communication

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Wireless multimedia sensor networks (WMSNs), with its exceptional properties, have found a sturdy and steady spot in automation and surveillance applications. The WMSN had made a massive drift of concentration from the wireless sensor networks with its capability of retrieving multimedia files through multimedia devices. The huge capacity data transfer through the multimedia sensors drain the power capacity of the sensors and is considered to be the vital challenge of the WMSNs. The challenges associated with the WMSNs are the restrictions in resources, connectivity, and security and maintaining a good level of quality of service (QoS). This paper proposes a novel protocol, optimized compressed sensing routing protocol (OCSRP), that performs the routing of multimedia data in a highly efficient manner through which the aforementioned research challenges like resource restrictions and QoS can be addressed. In addition, the security methods were incorporated in routing mechanism, and the results were compared with the existing LEACH algorithm. The quantitative analysis proves that the proposed model possesses high level of QoS with high level of security than the existing security algorithms.

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Pruned discrete Tchebichef transform for image coding in wireless multimedia sensor networks

Cited by 19 publications

References 17 publications

Image Compression Techniques in Wireless Sensor Networks: A Survey and Comparison

Image Compression Techniques in Wireless Sensor Networks: A Survey and Comparison

Multimedia Independent Multipath Routing Algorithms for Internet of Things Based on a Node Hidden Communication Model

Design of optimized compressed sensing routing protocol for wireless multimedia sensor networks

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