基于DCT的子带分解和SLCCA数据组织的嵌入式图像压缩

Junqiang Lan, X. Zhuang
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引用次数: 15

摘要

小波变换具有谐波空频局部化和能量压缩的优点,但计算复杂度普遍较高。本文采用8/spl次/8快速离散余弦变换(DCT)方法进行子带分解,然后进行SLCCA数据组织和熵编码。仿真结果表明,嵌入式DCT-SLCCA图像压缩将计算复杂度降低到小波子带分解的四分之一,而在相同比特率下,平均峰值信噪比(PSNR)仅下降0.6 dB。主观图像质量的下降几乎不明显。此外,由于8/spl倍/8快速DCT硬件实现已商品化,所提出的DCT- slcca具有高性能高速图像编码和传输的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Embedded image compression using DCT based subband decomposition and SLCCA data organization
Wavelet transform provides harmonic space-frequency localization and great energy compaction, but with generally high computational complexity. In this paper, an 8/spl times/8 fast discrete cosine transform (DCT) approach is adopted to perform subband decomposition, followed by SLCCA data organization and entropy coding. Simulation results showed that the embedded DCT-SLCCA image compression reduced the computational complexity to only a quarter of the wavelet based subband decomposition while the average peak signal-to-noise ratio (PSNR) degraded at the same bit rate by only 0.6 dB. The subjective image quality degradation was almost unnoticeable. Moreover, due to 8/spl times/8 fast DCT hardware implementation being commercially available, the proposed DCT-SLCCA has the potential for high performance high speed image coding and transmission.
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