A Hue-domain filtering technique for enhancing spatial sampled compressed sensing-based SAR images

Abstract

Millimeter-wave synthetic aperture radar (SAR) implementations need many sampling points that means huge data collection and long processing time. Owing to compressed sensing, SAR data can be easily reconstructed with fewer random samples than Shannon/Nyquist criteria. The most used sampling strategy is to select samples from all spatial-frequency SAR data. Since this type of sampling strategy requires many sampling probes that makes application impractical, sparse aperture sampling strategies have been proposed recently. However, a high noise ratio in spatial-sampled (SS) images is still a disturbing problem to be solved. In this study a novel Hue-domain filtering technique (HFT) is proposed to remove unwanted noises from SS-SAR images. For this purpose, reconstructed SAR images are transformed to the red, green, and blue, and hue, saturation, and value formats, respectively. Then the best threshold ratio to distinguish the noises from the targets is determined by means of the Otsu method. Thus, the mask containing only the target information is formed and applied to the SAR image. Thanks to the proposed technique, whole noise signs are removed without any target loss from the reconstructed image. The accuracy and effectiveness of the proposed HFT are verified by means of both visual comparison of the results and integrated side-lobe ratios of the real measurements.