Fusing remote sensing images using à trous wavelet transform and empirical mode decomposition
Pattern Recognition Letters
A method to eliminate riding waves appearing in the empirical AM/FM demodulation
Digital Signal Processing
Improved bi-dimensional EMD and Hilbert spectrum for the analysis of textures
Pattern Recognition
An oblique-extrema-based approach for empirical mode decomposition
Digital Signal Processing
On analysis of bi-dimensional component decomposition via BEMD
Pattern Recognition
IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
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An approach to analyze the period of a signal based on Hilbert-Huang Transform is presented in this paper. For an approximately periodic signal which contains plenty of high frequency components, the relation between its period and its main frequency is established. Our main result is that, for an approximately periodic signal which contains plenty of high frequency components, its period can be estimated accurately according to its main-frequency distribution. By applying the technique on texture analysis, a novel method to extract the perodicity features of a texture image is developed, which can be used in texture classification, segmentation, recognition and other applications.