Abstract
To increase the spatial resolution of passive microwave radiometry, mirrored aperture synthesis (MAS) was presented. In this letter, the method of cosine visibility extension (CVE) is proposed to further enhance the spatial resolution of 1-D MAS. In the CVE method, a convolutional neural network (CNN) is used to learn the distribution of the cosine visibility (CV), specifically the relationship between the low- and high-frequency CV distributions of various scenes. Then, the high-frequency CVs are estimated by the CNN according to the low-frequency CVs obtained by MAS. The high- and low-frequency CVs are combined in MAS image reconstruction to enhance the spatial resolution of MAS. The simulation and experiment indicate that the CVE method can effectively enhance the spatial resolution of MAS.
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.
