Wavelet Denoising by Quantum Threshold Algorithm
Peng Wang, Jianping Li · 2007
Quantum threshold algorithm is proposed to reduce the noise of signal. Quantum superposition principle is used to construct noise model in wavelet domain. We consider that signal is quasi quantum system. Every wavelet coefficient belongs to a superposition state. We don 't know whether it belongs signal or noise until we measure it. Unlike hard threshold algorithm quantum threshold algorithm hasn't a certain threshold. The probability that a wavelet coefficient belongs to signal or noise is decided by a distribution function. Finally, several experiments are made to compare the proposed method with conventional hard threshold algorithm. The pseudo-Gibbs phenomena can be reduced by this algorithm.