A fast mixing matrix estimation method in the wavelet domain

作者：Xu, Jin-dong; Yu, Xian-chuan^*; Hu, Dan; Zhang, Li-bao

来源：Signal Processing, 2014, 95: 58-66.

DOI：10.1016/j.sigpro.2013.08.014

• Blind image separation
• Single source points
• Sparse component analysis
• Latent Variable Analysis
• Wavelet transform

In the field of blind image separation (BIS) based on the sparse component analysis, separation efficiency and accuracy are directly affected by the number of clustering samples. To address this problem, a new algorithm for the detection of points in the Haar wavelet domain was proposed in which only single source contributions occur. The algorithm identified the single source points (SSPs) by comparing the absolute direction between the diagonal and horizontal components of the Haar wavelet coefficients of mixed images. After screening the SSPs, the wavelet coefficients of the images are sparser. The experimental results showed that, compared to the conventional method, the proposed algorithm could estimate the mixing matrix faster and more accurately, and it allowed identification of latent variables via statistical histograms.

• 出版日期2014-2
• 单位北京师范大学