Adaptive Threshold De-noising Based on Wavelet Transform
Hua Chen · Electric Power Science and Engineering · 2003
Denoising and restoring is a primary and basic work of signal processing. Its aim is to restore signals polluted by noise. Its outcome affects the subsequent signal processing. Some denoising methods on wavelet are discussed, such as decomposing and reconstructing method on wavelet, nonlinear threshold denoising method on wavelet, the translation invariant denoising method and the wavelet transform modulus maximum method. Adaptive threshold denoising on wavelet transform is preferred to nonlinear threshold denoising measure on wavelet. Simulation result shows that the denoising result is improved and it can be used in the signal processing with noise variation as time.