Efficient Architecture for Adaptive Directional Lifting-Based Wavelet Transform

被引:0
作者
Yin, Zan [1 ]
Zhang, Li [1 ]
Shi, Guangming [1 ]
机构
[1] Xidian Univ, Minist Educ, Key Lab Intelligent Percept & Image Understanding, Xian, Peoples R China
来源
VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2010 | 2010年 / 7744卷
关键词
ADL; paralleled architecture; pipelined architecture; FPGA;
D O I
10.1117/12.863506
中图分类号
TB8 [摄影技术];
学科分类号
0804 ;
摘要
Adaptive direction lifting-based wavelet transform (ADL) has better performance than conventional lifting both in image compression and de-noising. However, no architecture has been proposed to hardware implement it because of its high computational complexity and huge internal memory requirements. In this paper, we propose a four-stage pipelined architecture for 2 Dimensional (2D) ADL with fast computation and high data throughput. The proposed architecture comprises column direction estimation, column lifting, row direction estimation and row lifting which are performed in parallel in a pipeline mode. Since the column processed data is transposed, the row processor can reuse the column processor which can decrease the design complexity. In the lifting step, predict and update are also performed in parallel. For an 8x8 image sub-block, the proposed architecture can finish the ADL forward transform within 78 clock cycles. The architecture is implemented on Xilinx Virtex5 device on which the frequency can achieve 367 MHz. The processed time is 212.5 ns, which can meet the request of real-time system.
引用
收藏
页数:6
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