Detection and extraction of quasi-linear features in SAR images using a line segment image transform and inverse transform

Robert E. Hall

doi:10.1117/12.145516

28 May 1993 Detection and extraction of quasi-linear features in SAR images using a line segment image transform and inverse transform

Robert E. Hall

Author Affiliations +

Proceedings Volume 1875, Ultrahigh Resolution Radar; (1993) https://doi.org/10.1117/12.145516
Event: OE/LASE'93: Optics, Electro-Optics, and Laser Applications in Scienceand Engineering, 1993, Los Angeles, CA, United States

Abstract

A line segment image transform and inverse transform is used to detect and extract quasi- linear features in synthetic aperture radar (SAR) images. The transform is a windowed version of the Radon transform. The transform begins by dividing the original image into overlapped subimages using a simple analysis filter. 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. Line segments whose detection statistics are above a specified threshold are passed, and the filtered subimage is reconstructed using an inverse Radon transform (convolution back projection). Finally, the filtered subimages are recombined to form the filtered version of the original image. The filtering procedure passes quasi-linear features in the original image, and rejected features that are not quasi-linear, such as speckle. The inversion procedure is designed so that the original image is reconstructed if the threshold is set to zero.

Citation Download Citation

Robert E. Hall "Detection and extraction of quasi-linear features in SAR images using a line segment image transform and inverse transform", Proc. SPIE 1875, Ultrahigh Resolution Radar, (28 May 1993); https://doi.org/10.1117/12.145516

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available