An efficient SAR edge detector with a lower false positive rate

Abstract

An efficient ratio-based edge detector (RBED) is proposed for synthetic aperture radar (SAR) images to decrease the false positive detection rate. Low false rate is achieved by taking full advantage of the integrative information associated with multiple adjacent edge-pixels. The RBED introduces a novel 2D separable filter. The 2D filter is represented as the direct product between a 1D vertical filter and a 1D parallel filter. The vertical filter is heuristically designed as the product of a power function and a Gaussian function, simply called the power-modulated-Gaussian function with a weaker tail. Under the non-ideal edge model, this power-modulated-Gaussian vertical filter keeps the false positive rate low and provides a good localization precision. The parallel filter is set as a flat bell-shaped function that is designed by taking a good trade-off between the Gaussian function and the gate function. Such a flat bell-shaped parallel filter with two flexible parameters can be properly adjusted so that the false positive rate can further be decreased. The constant false alarm rate and localization bias of the RBED are analysed theoretically. A set of objective and subjective experiments demonstrate that the RBED can markedly decrease the false positive rate and obtain closed skeleton edges.

A Novel and Fast Corner Detection Method for Sar Imagery

“…A Gaussian template can suppress the noise to some extent. Moreover, local structural information has been taken into consideration in each template, the adjacent pixels can help us identify the candidate pixel more efficiently (Wei and Feng, 2015). Consequently, the proposed method is more stable and more robust to speckle noise.…”

UDR: An Approximate Unbiased Difference-Ratio Edge Detector for SAR Images

“…During the last twenty years, many specialized SAR edge detection methods have been proposed [14], [15], [16], [17]. Since speckle noise visually degrades the quality of SAR images and largely increases the difficulty of edge detection, most methods are mainly concerned with how to effectively detect edges with improved detection rate [17].…”

“…Besides the NSHT, several commonly used edge-pixel extraction methods, such as watershed algorithm in combination with thresholding of the basin dynamics or region merging and so on [26] [27], can be used to replace the NSHT. For a more detailed discussion on post-processing methods, we refer readers to [16] [17] and the references therein.…”

Distance-based edge detection on synthetic aperture radar imagery

“…Gambini et al (2008) compared five strategies based on SAR data or on estimates of the target roughness. Wei and Feng (2015), assuming a gamma model, derived a detector with low false alarm rate, but its performance strongly depends on the settings. Giron et al (2012) used a nonparametric approach with good results but, again, the performance is a ected by the underlying distribution of the data.…”