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Cycle I Adderl Shift I Adder2

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MEMl consists of two banks and MEM2 consists of four banks. The multi- bank structure increases the memory bandwidth and helps support highly pipelined operation. Details of the memory organization and size, register file, and schedule for the overall architecture with specific details for each constituent filter have been included in [27].

REFERENCES 133

Total time required to transform an N x N block using (5, 3) wavelet filter using this architecture is 2[N/2]

+

3T,

+

2T,

+

N

+

5

+

LN/2JN clock cycles, where T, is delay of an adder and T, is delay of a shifter. Any other type of wavelet filters can be efficiently executed in this architecture as well. Details of these filters and their timing for execution in this architecture have been presented in [27].

5.4 SUMMARY

In this chapter, we presented VLSI algorithms and architectures for discrete wavelet transforms. We described the traditional convolution (filtering) ap- proach for computation of discrete wavelet transform and described how a systolic architecture can be designed for wavelet filters by exploiting the sym- metric relationship of the filter coefficients. Since the lifting-based wavelet transform is a development of the late 1990s and is new in the VLSI commu- nity, we emphasized more on the VLSI architectures for the lifting-based DWT computation in this chapter. Lifting-based DWT has many advantages over the traditional convolution-based approach. It requires less memory and com- putation for implementation compared to the convolution-based approach.

We reviewed and presented the VLSI architectures that have been reported very recently for lifting-based DWT. We presented how the data-dependency diagram for the lifting computation can be mapped into pipelined architec- tures for suitable VLSI implementation, and proposed enhancement of the pipeline architectures by applying different schemes reported in the litera- ture. We described in greater detail a highly folded VLSI architecture for computation of both one-dimensional and two-dimensional transformations.

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