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Combined significance map coding for still image compression

机译:组合重要性图编码用于静止图像压缩

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摘要

Set partitioning in hierarchical trees (SPIHT) was known for its relatively simple implementation and flexible scalability when it is combined with discrete wavelet transform (DWT). The authors propose a method called combined significance map coding (CSMC) to improve the coding efficiency of SPIHT when used with block-based discrete cosine transform (DCT). CSMC groups some blocks and encodes the combined significance map of one to several blocks together. Lots of bits spent in significance map coding can be saved when the trees constructed with block DCT coefficients have similar locality. From our simulation results, CSMC improves significantly when in comparison with the original SPIHT coder using DWT and DCT. It also yields better performance than JPEG2000, and even outperforms the non-scalable H.264 intra-mode coder for some test images. No coding table is required, and fine rate/quality scalability property of SPIHT is still preserved.
机译:与离散小波变换(DWT)结合使用时,分层树中的集划分(SPIHT)以其相对简单的实现和灵活的可伸缩性而闻名。作者提出了一种称为组合重要性映射编码(CSMC)的方法,以在与基于块的离散余弦变换(DCT)结合使用时提高SPIHT的编码效率。 CSMC将一些块进行分组,并将一个到几个块的组合重要性映射图一起编码。当使用块DCT系数构造的树具有相似的局部性时,可以节省在重要性图编码中花费的大量比特。根据我们的仿真结果,与使用DWT和DCT的原始SPIHT编码器相比,CSMC有了显着改善。与JPEG2000相比,它还具有更好的性能,甚至在某些测试图像上也优于不可缩放的H.264帧内模式编码器。不需要编码表,并且仍然保留了SPIHT的优良速率/质量可伸缩性。

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