Image denoising research based on lifting wavelet transform and threshold optimization

In many application occasions, symmetry or antisymmetry of wavelet is fairly important to signal processing. In mid 1990s, Sweldens advanced the lifting wavelet transform. Compared with the first-generation wavelet, the lifting scheme could complete the wavelet transform currently without allocating additional memory, so it is easy to achieve with chips; the algorithm is simple and suitable for parallel processing, which makes the computation more fast; it could realize integral wavelet transform, which has wide potential applications. The paper analyzes the wavelet lifting algorithm and its poly-phase decomposition mechanism and approaches the image processing algorithm based on lifting wavelet transform. Since the structure of lifting wavelet is independent of Fourier transform, conducting image fusion by using the lifting wavelet could improve the processing speed and save memory.