Dual X-Tree Wavelet Image Coding

摘要：

The lack of directional selectivity has harmed the performance of traditional discrete wavelet transform based image coding, especially when the original image includes multidirectional textures. To offer a better compression ability for multidirectional textural images, a novel wavelet image coding scheme, called dual x-tree wavelet image coding is proposed in this paper. First, the 2-D dual-tree discrete wavelet transform (DDWT) is performed on the input image. Then the noise shaping procedure is exerted on the transform coefficients to get their sparse representation. Finally, an improved x-tree image coding algorithm is applied to encode the coefficients. Different from the common used noise shaping, we adopt a pruning phase to the procedure to make the coefficients better fit our dual x-tree encoder. To make good use of the strong correlation between two wavelet trees produced from DDWT, the dual wavelet trees are jointly encoded to improve the coding performance. Simulation results have demonstrated that the proposed algorithm achieves about 0.5dB gain over state-of-thearts for multidirectional textural image at low bitrate.

关键词： wavelet image coding dual-tree discrete wavelet transform noise shaping dual x-tree

作者: Li Li Canhui Cai

作者单位: School of Information Science and Engineering, Huaqiao University, Quanzhou, Fujian 362021, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 716-719

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）