This paper presents an efficient texture synthesis based on wavelet packet tree TSWPT. It has\r\nthe advantage of using a multiresolution representation with a greater diversity of bases functions\r\nfor the nonlinear time series applications such as fractal images. The input image is decomposed\r\ninto wavelet packet coefficients, which are rearranged and organized to form hierarchical trees\r\ncalled wavelet packet trees. A 2-step matching, that is, coarse matching based on low-frequency\r\nwavelet packet coefficients followed by fine matching based on middle-high-frequency wavelet\r\npacket coefficients, is proposed for texture synthesis. Experimental results show that the TSWPT\r\nalgorithm is preferable, especially in terms of computation time.
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