Video compression can reduce the amount of data information for wireless multimedia sensornetworks(WMSNs). Compared with the traditional video coding algorithms, big gap existed in coding performance for Distributed ...
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Video compression can reduce the amount of data information for wireless multimedia sensornetworks(WMSNs). Compared with the traditional video coding algorithms, big gap existed in coding performance for Distributed Video Coding (DVC). In order to improve the efficiency of side information estimation, a novel hash-based side information estimation algorithm is proposed in this paper. For the regions of the Wyner-Ziv frame which cannot coding and decoding accurately, Discrete Cosine Transform (DCT) low-frequency coefficients of DCT is extracted according to the criteria of ROI for entropy coding. Then decoded DCT low-frequency coefficients for bidirectional hash motion estimation is utilized by decoder, which enables the decoder to choose between past and future reference frames for frame interpolation to generate best side information. Experimental results show that our proposed algorithm can gain more accurate motion estimation in the intense motion region. The algorithm can also reduce the rate, improve the quality of decoded image, and decrease the energy consumption of sensor nodes ultimately, which is important for WMSNs.
Device-to-device (D2D) communication has been widely studied to improve network performance and been considered as a potential technological component for the next generation communication. As Quality of Experience (Q...
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ISBN:
(纸本)9781509015269
Device-to-device (D2D) communication has been widely studied to improve network performance and been considered as a potential technological component for the next generation communication. As Quality of Experience (QoE) is the major determining factor for the media service, we aim at promoting user's QoE Mean of Score (MOS) value for dynamic cellular networks. In this paper, we focus on the problem of heterogeneous media service distribution in D2D communications underlaying cellular networks. Firstly, we propose an innovative distributed media service scheme based on QoE models that jointly solve the massive media content dissemination issue for cellular networks. Moreover, our work maximizes users' QoE satisfaction by jointly considering media-aware, popularity function and priority function. Then, we propose a novel resource allocation algorithm based on the popularity function to optimize the total users' QoE satisfaction and avoid the influence of D2D interference. Numerical simulation results demonstrate the effectiveness of our proposed schemes.
This paper considers the problem of transmitting correlated information from multiple sources to multiple receivers, where every receiver seeks to recover all of the original sources. In order to improve the efficienc...
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To mitigate the severe effect of pilot contamination, a novel graph coloring (NGC) based algorithm is applied to pilot assignment in cell-free massive multiple-input multiple-output (MIMO) systems. Specifically, first...
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ISBN:
(纸本)9781665409513
To mitigate the severe effect of pilot contamination, a novel graph coloring (NGC) based algorithm is applied to pilot assignment in cell-free massive multiple-input multiple-output (MIMO) systems. Specifically, firstly, the potential pilot contamination intensity among users is calculated by utilizing the large-scale fading between users and access points (APs). Then, the contamination threshold is set to perform the sparsification and an interference graph describing the user interference relationship is constructed. Finally, the proposed algorithm is used to implement pilot assignment in the interference graph. In addition, an iterative grid search (IGS) approach is adopted to update the threshold to ensure that the system downlink sum-rate is maximized. The numerical results reveal that the proposed NGC pilot assignment algorithm with optimized thresholds can remarkably improve the system performance compared with previous pilot assignment schemes.
This paper presents a new method of gaze tracking based on iris detection for images of human eyes captured by ordinary PC camera. In the basis of traditional iris detection, this paper improves the circle detection b...
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For the current opportunistic networks routing algorithms, their message arrival rate is not high and the delivery delay is large. This paper proposes a domain-epidemic spray and forward routing algorithm. The algorit...
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In this paperwe propose a practical interference alignment (IA) scheme for the downlink cellular systems with multi-carrier transmission over multi-input-multi-output (MIMO) channels, where the interference is decompo...
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Graphical models have been widely applied in solving distributed inference problems in wirelesssensornetworks (WSNs). In this paper, we formulate the distributed multi-sensor tracking problem in a WSN as an inferenc...
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Graphical models have been widely applied in solving distributed inference problems in wirelesssensornetworks (WSNs). In this paper, we formulate the distributed multi-sensor tracking problem in a WSN as an inference problem on a factor graph. Using particle filtering methods, we propose a nonparametric variant of sum-product algorithm (SPA), called sequential particle-based SPA (SPSPA), for factor graphs to infer the multi-sensor target states over time. In the proposed algorithm, importance sampling methods are used to sample from message products, and the computational complexity of SPSPA is thus linear in the number of particles. We apply the SPSPA to a distributed multi-sensor tracking problem, and evaluate its performance in terms of the measurement noise and the number of particles.
To reduce time delay of processing data and improve the efficiency of cloud computing, a clustering algorithm based on the principle of minimum distance is proposed to place user-based and item-based data, update clus...
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ISBN:
(纸本)9781479959716
To reduce time delay of processing data and improve the efficiency of cloud computing, a clustering algorithm based on the principle of minimum distance is proposed to place user-based and item-based data, update cluster centre and the threshold dynamically. Besides, consistent hashing is combined to solve the fault tolerance and scalab.lity issues. In addition, Case-Based Reasoning (CBR) algorithm and item-based Coordination Filtering (CF) algorithms are used for filling sparse matrix to achieve better effect on the user-based clustering. Simulation results show that compared with data placement strategy based on K-means algorithm, this data placement strategy significantly improves clustering accuracy, greatly reduces delay of processing data and increases database scalab.lity and redundancy, thereby improving the efficiency of cloud computing.
Although deep learning has dominated the ship detection domain, it still has two challenges: arbitrary-oriented densely arranged ships cause detection omissions and large scale image contains redundant areas. This pap...
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ISBN:
(纸本)9781728123264
Although deep learning has dominated the ship detection domain, it still has two challenges: arbitrary-oriented densely arranged ships cause detection omissions and large scale image contains redundant areas. This paper proposes an effective convolutional neural network framework for arbitrary-oriented ship detection in large scale and complex scenes. In this framework, we propose Cumulative Feature Pyramid networks for multi-receptive-field feature fusion, which enhances high-level semantic information at all scales. Based on the outputs of Region Proposal networks, Rotation Region Locating network predicts rotation bounding box of arbitrary-oriented ships and adopts rotation intersection over union to avoid the effect of ship dense arrangement. For large scale scenes, No-Ship Area Suppression uses OTSU algorithm to generate binary mask and then filter out non-ship regions to reduce redundant computations. Additionally, we firstly build a remote sensing image dataset for ship detection, which contains 4237 images and over 21200 ships. Experimental comparisons with the state-of-the-art approaches validate the effectiveness, accuracy and robustness of the proposed method.
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