摘要
嵌入式零树小波编码方法(EZW)是目前公认的效率最高的小波图像编码方法之一.EZW算法中,不同的小波分解层数能够影响小波变换的时频分辨率和小波系数的变化范围,从而影响最终的编码效率;扫描次数的多少直接关系到能被编码的有效小波系数,从而影响最终的编码增益.讨论了EZW算法中小波分解层数和小波系数的扫描次数对图像压缩性能的影响,为基于EZW算法的小波图像压缩中的选择合适的小波分解层数及扫描次数提供了参考.通过仿真实验可以看出,在相同的扫描次数下,随着小波分解层数的增加,压缩比增大,而峰值信噪比随之下降;而在相同小波分解层数下,随着扫描次数的增加,峰值信噪比显著提升,而压缩比明显下降.
Embedded zero-tree wavelet encoding （EZW） algorithm is one of the well-known most efficient wavelet image encoding algorithms. In the EZW algorithm, different wavelet decomposition levels will affect the time-frequency resolution of the wavelet as well as the variation of the wavelet coefficients, therefore affecting the final encoding efficiency. Moreover, the times of scan will directly affect the wavelet coefficients to be encoded, therefore affecting the final encoding gain. In this paper, the effects of the wavelet decomposition levels and the times of the scan are investigated and discussed, therefore providing the instruction for the choices of the wavelet decomposition level and the times of scan in the EZW algorithm. From the experiments, we can see that in the same times of scan, with the increase of the wavelet decomposition levels, the image compression ratio （CR） increased accordingly, while the peak signal-to-noise ratio （PSNR） decreases. In the same wavelet decomposition level, with the increase of times of scan, the PSNR increases greatly while the CR decreases.
出处
《计算机系统应用》
2013年第8期130-135,共6页
Computer Systems & Applications
基金
国家自然科学基金(61102164)
杭州师范大学科研启动基金(2011QDL021)
杭州师范大学本科生创新能力提升工程项目
杭州师范大学实验室开放项目
杭州师范大学挑战杯项目
关键词
图像压缩
小波变换
EZW算法
小波分解
image compression
EZW algorithm
wavelet transform
wavelet decomposition
PSNR
