Improved SPIHT Algorithm for Texture Image Compression

Abstract:

Aiming at the problems of complicated convolution process of traditional wavelet transform and the unsatisfied effect of SPIHT algorithm for texture image compression, an improved SPIHT algorithm for texture image compression is proposed. At first, the texture image is decomposed into N order with the help of the lifting wavelet and the first-order high frequency sub-bands are decomposed into N-1 order by the lifting wavelet, and then the wavelet coefficients are encoded by the improved SPIHT algorithm. The improved SPIHT algorithm improved the process method of the wavelet coefficients in the low-frequency sub-bands and the detection method of some important coefficient in the L collection of the original SPIHT algorithm. Experiments show that the improved algorithm can retain the texture information of texture image more effectively and the quality of reconstructed image and peak signal to noise ratio are better than the original algorithm at the same rate. The effect is better especially at low rate, so the improved algorithm is an efficient compression method for texture image.

• Periodical: Applied Mechanics and Materials (Volume 619)
• Pages: 311-315
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.619.311
• Online since: August 2014
• Authors: Bao Xia Cui, Yun Ze Wu
• Keywords: Image Compression, Lifting Wavelet, SPIHT, Texture Image, Wavelet Transform (WT)

References

[1] Yonghong Wu, Donghui Li and Jing Liu. Study of the lossless image compression method based on improved SPIHT[J]. Control and Automation Publication Group, Vol. 28, No. 3 (2012), pp.142-144.

[2] Amir Said, William A. Pearlman. A new, fast, and efficient image codec based on set partitioning in hierarchical trees [J]. IEEE Transactions on Circuits and Systems for Video Technology, Vol. 6 ，No. 3 (1996), pp.243-250.

DOI: 10.1109/76.499834

[3] Min Tang, Xiumei Chen and Feng Chen. Colorful medical image compression based on contourlet transform and SPIHT algorithm[J]. Computer Science, Vol. 41, No. 1 (2014), pp.303-306.

[4] Lu Wang, Zhimin Zhang. SAR image compression based on modified SPIHT[J]. The Chinese Academy of Sciences of Graduate School, Vol. 29, No. 2 (2012), pp.220-226.

[5] Yanchun Yang, Jianwu Dang and Yangping Wang. A medical image fusion method based on lifting wavelet transform and adaptive PCNN[J]. Journal of Compute-Aided Design & Computer Graphics, Vol. 24, No. 4 (2012), pp.494-499.

[6] Qu Gong, Ruan Hua. Image compression based on integer lifting wavelet transform and improved SPIHT[J]. Computer Simulation, Vol. 26, No. 3 (2009), pp.195-197.