Any remote sensing image regardless of the source (satellite, aircraft or any sensors and platforms) from which it is acquired undergoes distortion. This generally happens because of the various aspects concerning the optics, scanning mechanism; or motion, velocity, altitude and attitude associated with platforms or may be due rotations and curvature of the earth. Synthetic Aperture Radar (SAR) imaging is one of the emerging technology of remote sensing which has grabbed the attention of most of the researchers. Also, in recent years Compressed Sensing (CS) theory has emerged in both signal processing and image processing domains. Compressed sensing promises image reconstruction at a lower sampling rate than traditional Nyquist sampling and hence CS can also be used for image retrieval. Not only this but CS also provides a faster and efficient way to reproduce the signals. This paper demonstrates the application of CS theory for pre-processing on high-resolution images for SAR image reconstruction.
Pre-processing of SAR Images through Compressed Sensing
2019-06-01
1099589 byte
Conference paper
Electronic Resource
English
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