A muitisensor image fusion algorithm is described using 2-dimensional nonseparable wavelet frame （NWF） transform. The source muitisensor images are first decomposed by the NWF transform. Then, the NWF transform coef...A muitisensor image fusion algorithm is described using 2-dimensional nonseparable wavelet frame （NWF） transform. The source muitisensor images are first decomposed by the NWF transform. Then, the NWF transform coefficients of the source images are combined into the composite NWF transform coefficients. Inverse NWF transform is performed on the composite NWF transform coefficients in order to obtain the intermediate fused image. Finally, intensity adjustment is applied to the intermediate fused image in order to maintain the dynamic intensity range. Experiment resuits using real data show that the proposed algorithm works well in muitisensor image fusion.展开更多
正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)调制因其高效的频带利用率和良好的抗多径能力广泛用于合作与非合作通信系统中。合作通信场景下,通常接收机可以利用已知帧结构实现OFDM信号的检测。但在非合作场景下,...正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)调制因其高效的频带利用率和良好的抗多径能力广泛用于合作与非合作通信系统中。合作通信场景下,通常接收机可以利用已知帧结构实现OFDM信号的检测。但在非合作场景下,接收机没有足够的先验信息,导致帧检测难度加大。针对这一问题,提出了一种适合于非合作通信场景的OFDM数据帧的检测算法。所提算法利用快速小波变换将含噪OFDM信号的功率包络进行小波分解与重构,对重构得到的功率包络进行差分运算后,再通过与阈值比较实现OFDM信号的帧检测。相较于混合能量检测算法,所提算法计算预设参数少,复杂度低。仿真结果表明,所提算法在加性高斯白噪声信道和多径衰落信道下带内信噪比分别取-6 dB和3 dB时即可实现零漏报率,且零漏报率的阈值选取范围比混合能量检测算法扩大了约6 dB。展开更多
文摘A muitisensor image fusion algorithm is described using 2-dimensional nonseparable wavelet frame （NWF） transform. The source muitisensor images are first decomposed by the NWF transform. Then, the NWF transform coefficients of the source images are combined into the composite NWF transform coefficients. Inverse NWF transform is performed on the composite NWF transform coefficients in order to obtain the intermediate fused image. Finally, intensity adjustment is applied to the intermediate fused image in order to maintain the dynamic intensity range. Experiment resuits using real data show that the proposed algorithm works well in muitisensor image fusion.
