This paper aims at introducing the recent theory of compressive sensing to radar imaging systems in order to retrieve the imaged scene with better resolution and a reduced amount of collected samples. As a result of the application of the alternative imaging technique proposed, the use of matched filtering is avoided and the effect of its sidelobes in the images is drastically diminished. Furthermore, the amount of data to be stacked in the sensor and then downlinked to the ground station is meaningfully lower. This permits a more efficient management of resources.

Abstract-This paper presents a novel technique for automatic edge enhancement and detection in synthetic aperture radar (SAR) images. The characteristics of SAR images justify the importance of an edge enhancement step prior to edge detection. Therefore, this paper presents a robust and unsupervised edge enhancement algorithm based on a combination of wavelet coefficients at different scales. The performance of the method is first tested on simulated images. Then, in order to complete the automatic detection chain, among the different options for the decision stage, the use of geodesic active contour is proposed. The second part of this paper suggests the extraction of the coastline in SAR images as a particular case of edge detection. Hence, after highlighting its practical interest, the technique that is theoretically presented in the first part of this paper is applied to real scenarios. Finally, the chances of its operational capability are assessed.Index Terms-Edge detection, geodesic active contour, synthetic aperture radar (SAR), wavelet transform.