基于Fpga的基于提升CDF(2,2)的高效并行结构图像压缩

K. Kumar, R. C. Joshi, A. Saxena
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引用次数: 0

摘要

提出了一种改进的二维离散小波变换(2D-DWT)结构,利用基于线的方法实现双正交Cohen-Daubechies-Feuvear(2,2)小波,并利用提升方案在FPGA上实现。基于FPGA的硬件实现尤其受益于架构的高并行性和保持数学模型定性效果所需的中等数字精度。所提出的架构被设计为每个时钟周期同时生成4个子带系数,可以在精确的工作时钟周期内对图像执行1级分解,在列处理器上没有任何行缓冲区,从而减少了行缓冲的时间,但增加了一个额外的行处理器,并且硬件利用率达到100%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FPGA BASED EFFICIENT PARALLEL ARCHITECTURE OF LIFTING BASED CDF (2,2) FOR IMAGE COMPRESSION
An improved architecture for two-dimensional discrete wavelet transform (2D-DWT) to implement bi-orthogonal Cohen-Daubechies-Feuvear (CDF) (2,2) wavelet with line-based method is proposed for FPGA implementation using lifting scheme. The FPGA based hardware implementation profits especially from the high parallelism in the architecture and the moderate number precision required to preserve the qualitative effects of the mathematical models.  The proposed architecture is designed to generate 4 sub bands coefficients concurrently per clock cycle that can perform a 1-level decomposition of a  image in exactly  working clock cycles, without any line buffers at the column processor, thus reducing the time for line buffering but with an extra row processor and with 100% hardware utilization.
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