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作为小波变换的一般化推广,小波包(WP)为自适应波形分析提供了一个有效的表示工具.最近的研究表明基于小波包的图像编码算法相对基于小波的在性能上有较大提高.然而过去的许多工作都采纳了一种树结构的量化技术,这种技术对于小波图像编码很成功,但并不适宜于小波包子带.利用率失真最优化的小波包分解技术以及子带内的块分割编码方法,提出了一个静止图像编码算法.在这个算法中,每一个小波包子带都通过块分割编码技术和JPEG2000上下文模型单独进行编码,经由这种编码方式,自然地避免了当采用树结构量化方法时所必须面对的定义小波包系数间父子关系的困难.实验结果表明所提出的算法在客观质量评价(PSNR)及视觉质量上都比SPIHT和JPEG2000有很大提高,同时还优于当前高性能的小波包图像编码算法.
As a generalization of wavelet transform, wavelet packet (WP) provides an effective representation tool for adaptive waveform analysis.Recent studies show that the wavelet packet-based image coding algorithm is greatly improved in performance compared to wavelet Much work in the past has adopted a tree structure quantization technique which is very successful for wavelet image coding but not suitable for wavelet packet subbands. The wavelet packet decomposition technique for optimizing the utilization distortion and the intra- Segmentation coding method, a static image coding algorithm is proposed.In this algorithm, each wavelet packet sub-band coding technology through the block partition coding and JPEG2000 context model alone encoding, through this coding method, which naturally avoids the use of tree structure The difficulty of defining the parent-child relationship between wavelet packet coefficients must be met when quantifying the method. Experimental results show that the proposed algorithm is superior to SPIHT and JPEG2000 both in objective quality evaluation (PSNR) and visual quality Current high performance wavelet packet image coding algorithm.