Wavelet Denoising-Based Image Feature Extraction by Independent Component Analysis without Pre-Whitening
Xing Jia Tang, Xiu Fang Zhang · Applied Mechanics and Materials · 2013
This paper proposes an ICA image feature extraction method without pre-whitening based on wavelet denoising. Firstly, we conduct denoising for noisy observed images with wavelet transformation; then the feature extraction for denoised observed images is done by using FastICA algorithm without pre-whitening; finally, we further remove the residual noise in extracted feature images with wavelet transformation. Simulation experiment results show that this method is apparent in the performance of denoising, meanwhile, the extracted feature images can distinguish the texture and shape feature well, which has stronger practicability and validity.