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Dual-Scan Parallel Flipping Architecture for a Lifting-Based 2-D Discrete Wavelet Transform

Dual-Scan Parallel Flipping Architecture for a Lifting-Based 2-D Discrete Wavelet Transform
Abstract—An efficient dual-scan parallel flipping architecture for a lifting-based 2-D discrete wavelet transform is presented. The proposed novel algorithm is based on a flipping technique to implement a modular and hardware-efficient architecture with a very simple control path. In the proposed algorithm, the serial operation of the lifting data flow is optimized using parallel computations of independent paths in advance with pipeline operation to minimize the critical path to one multiplier delay and to achieve 100% hardware utilization efficiency.

The basic principle is to break up the polyphase matrix of the wavelet filters into a sequence of alternating upper and lower triangular matrices and a diagonal normalization matrix. According to the basic principle, the polyphase matrix of a 9/7 lifting filter is expressed as,
where α(1 + z−1) and γ(1 + z−1) are the predict polynomials, β(1 + z) and δ(1 + z) are the update polynomials, and K is the scale normalization factor. The 9/7 lifting filter coefficients are α = −1.586134342, β=−0.052980118, γ=0.8829110762, and δ=0.4435068522, and the scaling coefficient is K = 1.149604398. Given input sequence x(n), with n = 0, 1, . . . , N − 1, the lifting algorithm steps are given by,
Outputs di and si are the high-pass and low-pass wavelet coefficients.

Fig. 1. Architecture block diagram.
Equations (2)–(4) and (6) can be written after rearranging as,
Project Design Flow,

  • Select input image
  • Convert into pixel values using Matlab
  • Select even and odd location pixels
  • Choose filter type and take the α,β,γ,δ values
  • Apply DWT filter process according to equation 10-15
  • Get the values of Si and di
  • Repeat the same process for whole image
  • Display Wavelet Image
Simulation Video Demo 

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