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New Virtual SPIHT Tree Structures for Very Low Memory Strip-Based Image Compression

机译:新的虚拟SPIHT树结构,用于基于内存条的低内存图像压缩

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摘要

Images obtained with wavelet-based compression techniques such as set-partitioning in hierarchical trees (SPIHT) yield very good results. However, a lot of memory space is required as the wavelet coefficients for the whole image need to be stored for the process of set-partitioning coding. In this letter, we propose new virtual SPIHT tree structures for very low memory strip-based image compression. The advantage of the proposed work is that it reduces the memory requirements for practical software and hardware implementations significantly without sacrificing performance.
机译:使用基于小波的压缩技术(例如层次树中的集划分(SPIHT))获得的图像会产生非常好的结果。但是,由于集分配编码处理需要存储整个图像的小波系数,因此需要大量的存储空间。在这封信中,我们提出了新的虚拟SPIHT树结构,用于基于内存条的低内存图像压缩。提出的工作的优点在于,它在不牺牲性能的情况下,大大降低了实际软件和硬件实现的内存需求。

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