一种高效的基于空间预测的图像压缩方案

Chin-Hwa Kuo, Tzu-Chuan Chou, Tay-Shen Wang
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引用次数: 20

摘要

本文提出了一种高效的基于空间预测的渐进图像压缩方案。该方案包括两个阶段,即预测阶段和量化阶段。在预测阶段,利用最近邻像素的信息来预测中心像素。接下来进行就地处理,即,结果预测错误存储在与预测像素相同的内存位置中。因此,在编码过程和解码过程中所需的临时存储空间都大大减少。该预测方案生成具有层次结构的预测误差图像,可以利用现有的多种量化方案的结果,如EZW和SPIHT算法。因此,以一种直接的方式获得了渐进编码特征。在量化阶段,我们扩展了多级阈值方案。不仅考虑了像素强度值本身,而且还考虑了级别显著性。实验结果表明,该方案具有较好的压缩质量。它优于几种现有的图像压缩方案。此外,该方案仅通过整数加法和移位操作即可实现。实现了大量的计算节省。上述特点使得所提出的图像压缩方案有利于在有限带宽和低计算能力环境下的实时应用和无线传输领域。
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An efficient spatial prediction-based image compression scheme
An efficient spatial prediction-based progressive image compression scheme is developed in this paper. The proposed scheme consists of two phases, namely, the prediction phase and the quantization phase. In the prediction phase, information of the nearest neighbor pixels is utilized to predict the center pixel. Next in-place processes are taken, i.e., the resulting prediction error is stored in the same memory location as the predicted pixel. Thus, the temporary storage space required is significantly reduced in the encoding process as well as decoding process. The prediction scheme generates prediction error images with hierarchical structure, which can employ the result of many existing quantization schemes, such as EZW and SPIHT algorithms. As a result, a progressive coding feature is obtained in a straightforward manner. In the quantization phase, we extend the multilevel threshold scheme. Not only the pixel intensity value itself but also level significance is taken into account. In the experimental testing, we illustrate that the proposed scheme yields compression quality advantages. It outperforms several existing image compression schemes. Furthermore, the proposed scheme can be realized by only integer addition and shift operations. Tremendous amounts of computation-saving are achieved. The above features make the proposed image compression scheme beneficial to the areas of real-time applications and wireless transmission in limited bandwidth and low computation power environments.
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