The radon transform is commonly used in algorithms for detecting linear features in an image. However, it can have difficulty detecting line segments that are significantly shorter than the image dimensions, and has no capability of providing information about the positions of the endpoints of these shorter line segments, or on line length. These problems are magnified when the transform is applied to an image with a high level of noise. Our localization of the radon transform reduces the spatial extent of the image intensity integration, to improve the detection and localization of short line segments. This localized radon transform forms the basis of a linear feature detection algorithm that is demonstrated on several synthetic images containing various levels of random noise and on actual images containing linear features. Our experimental results demonstrate the ability of this approach to successfully detect the linear components of ship wakes visible in SAR ocean imagery.
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