High speed VLSI architecture for 2-D lifting Discrete Wavelet Transform

The lifting scheme reduces the computational complexity for computing Discrete Wavelet Transform (DWT) compared to convolution. We have proposed a high performance and memory efficient architecture with parallel scanning method for 2-D DWT using 5/3 Lifting wavelet. This 2-D architecture is composed with two 1-D DWT units and a Transpose Unit (TU). Proposed parallel scanning reduces requirement of on-chip line buffer compared to other line based scanning. Proposed 2-D DWT architecture utilizes only 2N size buffer for NxN sized image, which is low compare to 3.5N usual requirement for to implement 5/3 Lifting wavelet. This is achieved by performing column and row transform simultaneously. Designed 1-D DWT module can process two inputs at a time and produce two outputs per clock which reduces latency significantly compared to other 2-D dual scan based DWT architectures. Designed TU operates at half clock rate which reduces power and its design is independent of size of input image. Instead of shifter we propose Hardwired Scaling Unit (HSU) for coefficient multiplication. Unlike shift register unit this design saves clocks and helps in reducing power by great amount. This architecture is synthesized using Xilinx ISE 10.1 and is implemented on Virtex-IIPRO XC2VP30 FPGA. Very low FPGA resource utilization is found.

[1]  Liang-Gee Chen,et al.  Lifting based discrete wavelet transform architecture for JPEG2000 , 2001, ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196).

[2]  Liang-Gee Chen,et al.  Flipping structure: an efficient VLSI architecture for lifting-based discrete wavelet transform , 2002, Asia-Pacific Conference on Circuits and Systems.

[3]  Chengyi Xiong,et al.  Efficient Architectures for Two-Dimensional Discrete Wavelet Transform Using Lifting Scheme , 2007, IEEE Transactions on Image Processing.

[4]  Bruce F. Cockburn,et al.  Efficient architectures for 1-D and 2-D lifting-based wavelet transforms , 2004, IEEE Transactions on Signal Processing.

[5]  Liang-Gee Chen,et al.  Memory analysis and architecture for two-dimensional discrete wavelet transform , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  I. Daubechies,et al.  Factoring wavelet transforms into lifting steps , 1998 .

[7]  Bing-Fei Wu,et al.  A high-performance and memory-efficient pipeline architecture for the 5/3 and 9/7 discrete wavelet transform of JPEG2000 codec , 2005, IEEE Transactions on Circuits and Systems for Video Technology.

[8]  Marco Ferretti,et al.  A Parallel Architecture for the 2-D Discrete Wavelet Transform with Integer Lifting Scheme , 2001, J. VLSI Signal Process..

[9]  Chaitali Chakrabarti,et al.  A VLSI architecture for lifting-based forward and inverse wavelet transform , 2002, IEEE Trans. Signal Process..

[10]  Manuel P. Malumbres,et al.  On the Design of Fast Wavelet Transform Algorithms With Low Memory Requirements , 2008, IEEE Transactions on Circuits and Systems for Video Technology.