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Multispectral image compression and encryption method based on tensor decomposition in wavelet domain
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作者 XU Dongdong DU Limin DU Yunlong 《High Technology Letters》 EI CAS 2024年第3期244-251,共8页
Multispectral image compression and encryption algorithms commonly suffer from issues such as low compression efficiency,lack of synchronization between the compression and encryption proces-ses,and degradation of int... Multispectral image compression and encryption algorithms commonly suffer from issues such as low compression efficiency,lack of synchronization between the compression and encryption proces-ses,and degradation of intrinsic image structure.A novel approach is proposed to address these is-sues.Firstly,a chaotic sequence is generated using the Lorenz three-dimensional chaotic mapping to initiate the encryption process,which is XORed with each spectral band of the multispectral image to complete the initial encryption of the image.Then,a two-dimensional lifting 9/7 wavelet transform is applied to the processed image.Next,a key-sensitive Arnold scrambling technique is employed on the resulting low-frequency image.It effectively eliminates spatial redundancy in the multispectral image while enhancing the encryption process.To optimize the compression and encryption processes further,fast Tucker decomposition is applied to the wavelet sub-band tensor.It effectively removes both spectral redundancy and residual spatial redundancy in the multispectral image.Finally,the core tensor and pattern matrix obtained from the decomposition are subjected to entropy encoding,and real-time chaotic encryption is implemented during the encoding process,effectively integrating compression and encryption.The results show that the proposed algorithm is suitable for occasions with high requirements for compression and encryption,and it provides valuable insights for the de-velopment of compression and encryption in multispectral field. 展开更多
关键词 multi-spectral image compression encryption Lorenz three-dimensional chaotic mapping Arnold scrambling transform fast Tucker decomposition
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A pre-generated matrix-based method for real-time robotic drilling chatter monitoring 被引量:10
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作者 Jianfeng TAO Chengjin QIN +2 位作者 Dengyu XIAO Haotian SHI Chengliang LIU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2019年第12期2755-2764,共10页
Currently, due to the detrimental effects on surface finish and machining system, chatter has been one crucial factor restricting robotic drilling operations, which improve both quality and efficiency of aviation manu... Currently, due to the detrimental effects on surface finish and machining system, chatter has been one crucial factor restricting robotic drilling operations, which improve both quality and efficiency of aviation manufacturing. Based on the matrix notch filter and fast wavelet packet decomposition, this paper presents a novel pre-generated matrix-based real-time chatter monitoring method for robotic drilling. Taking vibration characteristics of robotic drilling into account, the matrix notch filter is designed to eliminate the interference of spindle-related components on the measured vibration signal. Then, the fast wavelet packet decomposition is presented to decompose the filtered signal into several equidistant frequency bands, and the energy of each sub-band is obtained. Finally, the energy entropy which characterizes inhomogeneity of energy distribution is utilized as the feature to recognize chatter on-line, and the effectiveness of the presented algorithm is validated by extensive experimental data. The results show that the proposed algorithm can effectively detect chatter before it is fully developed. Moreover, since both filtering and decomposition of signal are implemented by the pre-generated matrices, calculation for an energy entropy of vibration signal with 512 samples takes only about 0.690 ms. Consequently, the proposed method achieves real-time chatter monitoring for robotic drilling, which is essential for subsequent chatter suppression. 展开更多
关键词 Aviation manufacturing fast wavelet packet decomposition Matrix notch filter Real-time chatter monitoring Robotic drilling operations
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