Nonlinear filtering technique for the extraction of quasi-linear features from images
Robert Ernest Hall · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1993
A nonlinear filtering technique is developed for the extraction of quasi-linear features from images. The technique begins with a line segment image transform, which is a windowed version of the radon transform. The original image is divided into overlapped subimages using a simple analysis filter, and a radon transform is applied to each subimage, yielding a representation of the subimage in terms of line segments at varying angles and positions. The amplitude of each line segment is used to calculate the detection statistic for that line segment. A nonlinear filter is used to pass line segments whose detection statistics are above a specified threshold (it is shown that a threshold is an optimal Bayes estimate when the signal is intermittent). The filtered subimage is then reconstructed.