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Design method of measurement matrix for compressive sensing in wireless sensor network
LIU Yanxing, DANG Xiaochao, HAO Zhanjun, DONG Xiaohui
Journal of Computer Applications    2015, 35 (11): 3043-3046.   DOI: 10.11772/j.issn.1001-9081.2015.11.3043
Abstract729)      PDF (791KB)(650)       Save
In order to solve the problem of redundancy and transmission energy consumption in the process of data acquisition in wireless sensor networks, a method for designing the measurement matrix of compressive sensing was proposed in this paper. The method is based on the linear representation theory of diagonal matrix orthogonal basis and the process of constructing the matrix is simple with short time, high sparsity and low redundancy, which is very suitable for the nodes with limited hardware resources. The simulation results show the measurement method based on the linear representation theory of diagonal matrix gains higher signal recovery rate compared with Gauss random matrix and part Hadamard matrix under the same signal reconstruction accuracy. This method in the paper greatly reduces the traffic of networks, saves the network energy consumption and prolongs the network life cycle.
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Noise face hallucination via data-driven local eigentransformation
DONG Xiaohui GAO Ge CHEN Liang HAN Zhen JIANG Junjun
Journal of Computer Applications    2014, 34 (12): 3576-3579.  
Abstract179)      PDF (840KB)(638)       Save

Concerning the problem that the linear eigentransformation method cannot capture the statistical properties of the nonlinear facial image, a Data-driven Local Eigentransformation (DLE) method for face hallucination was proposed. Firstly, some samples most similar to the input image patch were searched. Secondly, a patch-based eigentransformation method was used for modeling the relationship between the Low-Resolution (LR) and High-Resolution (HR) training samples. Finally, a post-processing approach refined the hallucinated results. The experimental results show the proposed method has better visual performance as well as 1.81dB promotion over method of locality-constrained representation in objective evaluation criterion for face image especially with noise. This method can effectively hallucinate surveillant facial images.

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