Low Bit-Rate Image Compression via Discrete Wavelet Transform and Classified Vector Quantization

摘要：

This paper proposes a high-efficiency low bit-rate image compression algorithm that is based on weighted classified vector quantization (WCVQ) of discrete wavelet transform (DWT) coefficients. The algorithm first does multilevel wavelet decomposition to the original image, and then constructs band-cross vectors along resolution-level-cross high frequency sub-bands respectively in the horizontal, vertical and diagonal three directions that makes the most of the correlation of DWT coefficients among those subbands, and then classifies these band-cross vectors into important clustering and unimportant clustering by zero-tree vector and vector energy, and last merges several adjacent unimportant vectors into an unimportant vector block and codes them uniformly, while, applies weighted vector quantization consistent with HVS to the important vectors by progressive constructive clustering (PCC) algorithm that improves the coding efficiency and the reconstructed image quality.

关键词： DWT band-cross vectors construction vector classification weighted vector quantization PCC

作者: Huijie Guo Baojun Zhao

作者单位: School of Information and Electronics, Beijing Institute of Technology Beijing, China

会议类型: 国际会议

会议名称: 2010 International Conference on Signal and Information Processing(2010年IEEE信号与信息处理国际会议 ICSIP2010)

会议地点: 长沙

会议语种:英文

页码: 29-32

在线出版日期: 2010-12-14（万方平台首次上网日期，不代表论文的发表时间）