Abstract
Wavelet transform and principal component analysis based clutter reduction scheme is proposed for through wall imaging which is capable of discriminating between target, noise and clutter signals. Principal component analysis is used to reduce clutter and wavelet transform is used to further suppress noise signals (which results in enhancement of target signals). Proposed scheme significantly work well especially for extracting multiple targets in heavy clutters. Selection of different parameters (like mother wavelet, threshold type, threshold parameter, decomposition level and filter order etc) are explored for TWI. Existing and proposed schemes are compared on the basis of mean square error, peak signal to noise ratio and visual inspection.
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.
