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Proceedings Paper

Efficient architecture for adaptive directional lifting-based wavelet transform
Author(s): Zan Yin; Li Zhang; Guangming Shi
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Paper Abstract

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 8×8 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.

Paper Details

Date Published: 4 August 2010
PDF: 6 pages
Proc. SPIE 7744, Visual Communications and Image Processing 2010, 77442Q (4 August 2010); doi: 10.1117/12.863506
Show Author Affiliations
Zan Yin, Xidian Univ. (China)
Li Zhang, Xidian Univ. (China)
Guangming Shi, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 7744:
Visual Communications and Image Processing 2010
Pascal Frossard; Houqiang Li; Feng Wu; Bernd Girod; Shipeng Li; Guo Wei, Editor(s)

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