结合DPCM和DWT的霍夫曼图像压缩

Q3 Computer Science
M. Abo-Zahhad, R. Gharieb, Sabah M. Ahmed, M. Abd-Ellah
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引用次数: 24

摘要

提出了一种医学图像压缩方法。该方法首先对图像进行差分脉冲编码调制器(DPCM)预处理,然后对DPCM输出进行小波变换,最后对得到的系数进行霍夫曼编码。因此,这种方法理论上提供了三倍的压缩。仿真结果比较了所提出的(DPCM-DWT-Huffman)方法与合并DPCM (DPCM-Huffman)、DWT-Huffman和单独使用Huffman编码的Huffman方法的性能。计算了几个量化指标来衡量四种算法的性能。结果表明,DPCM-DWT-Huffman、DWT-Huffman、DPCM-Huffman和Huffman算法的压缩比(CR)分别为6.4837、4.32、2.2751和1.235。结果还证实,虽然所提出的DPCM-DWT-Huffman方法增强了CR,但与DWT-Huffman, DPCM-Huffman和Huffman算法相比,它不会降低其他性能量化指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Huffman Image Compression Incorporating DPCM and DWT
This paper presents a medical image compression approach. In this approach, first the image is preprocessed by Differential Pulse Code Modulator (DPCM), second, the output of the DPCM is wavelet transformed, and finally the Huffman encoding is applied to the resulting coefficients. Therefore, this approach provides theoretically threefold compression. Simulation results are presented to compare the performance of the proposed (DPCM-DWT-Huffman) approach with the performances of the Huffman incorporating DPCM (DPCM-Huffman), the DWT-Huffman and the Huffman encoding alone. Several quantitative indexes are computed to measure the performance of the four algorisms. The results show that the DPCM-DWT-Huffman, the DWT-Huffman, the DPCM-Huffman and the Huffman algorisms provide compression ratio (CR) of 6.4837, 4.32, 2.2751 and 1.235, respectively. The results also confirm that while the proposed DPCM-DWT-Huffman approach enhances the CR, it does not deteriorate other performance quantitative measures in comparison with the DWT-Huffman, the DPCM-Huffman and the Huffman algorisms.
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CiteScore
3.20
自引率
0.00%
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