Method for extracting road in SAR image

Abstract

The invention provides a method for extracting a road in an SAR image, which comprises the following steps of: carrying out early stage processing on an SAR image and adjusting contrast ratio and luminance; carrying out binarization on the SAR image after early stage processing so as to carry out filter processing in the following step; carrying out mathematic morphological filtration on the binarized SAR image so that the SAR image is more smooth and clean; carrying out road geometrical filtration on the SAR image after mathematic morphological filtration to remove a false-alarm area; carrying out Canny operator processing on the SAR image after road geometrical filtration to search the edge of the road; and finally extracting the road from the SAR image by detecting road through Hough conversion. By processing in all the steps, the road area in the SAR image can be extracted, the calculated amount is smaller, and the SAR image can be more rapidly processed; and a main road can be more rapidly extracted basically by automation and less manual intervention.

Description

technical field [0001] The invention relates to an image extraction method, in particular to a road extraction method in a SAR image. Background technique [0002] Road extraction in images can be divided into two categories according to the different ways of interaction. One type only gives the initial point and initial direction, and uses the tracking method to extract the road; the other type of method is given a series of scattered seed points, and uses the active contour model, simulated annealing and dynamic programming to extract the road by curve fitting. center line. The former mainly uses local features. The latter often seeks the global minimum energy. [0003] In the first method, the initial point and the initial road are given, and the centerline and sideline of the road are obtained by tracking. The problems to be solved include how to use the detected information to predict the parameters of the road at the next point (position, width, curvature, directio...

AI Technical Summary

Problems solved by technology

[0008] (1) In the dynamic programming method, the selection of seed points needs to be done manually, which is cumbersome, and this method requires a large amount of storage;

[0009] (2) The Snake model method has completed the task of road extraction to a certain extent, but the algorithm complexity is large, the calculation time is long, and the algorithm is sensitive to parameters

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