Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
