Circular array targets detection from remote sensing images based on saliency detection

Xianwei Han; Yili Fu

doi:10.1117/1.OE.51.2.026201

27 February 2012 Circular array targets detection from remote sensing images based on saliency detection

Xianwei Han, Yili Fu

Author Affiliations +

Optical Engineering, Vol. 51, Issue 2, 026201 (February 2012). https://doi.org/10.1117/1.OE.51.2.026201

Abstract

To extract circular array targets from high-spatial resolution optical satellite images, we propose an efficient two-step detection framework. In the first stage, we propose a multiscale histogram contrast (MHC) saliency evaluation model to detect salient objects. This saliency model is able to highlight all salient areas with well-defined boundaries and effectively suppress the obvious background textures. Moreover, the generated saliency map can be used to find the locations of potential targets most likely causing visual attention, which greatly decreases the computation cost in later processes. In the second stage, we extract task-related targets from these salient objects by removing the irrelevant salient areas according to the special properties of the targets. In this paper, we present a circular array targets-detection method based on the saliency map produced by the proposed saliency detector. First we extract the circular objects from the saliency map using simple shape features, which are then clustered through a graph-based approach to locate the target areas. To evaluate the performance of our saliency model and targets extraction scheme, we carried out many experiments on large-field, high-spatial resolution remote-sensing images and achieved promising results both in efficiency and precision.

Citation Download Citation

Xianwei Han and Yili Fu "Circular array targets detection from remote sensing images based on saliency detection," Optical Engineering 51(2), 026201 (27 February 2012). https://doi.org/10.1117/1.OE.51.2.026201

Published: 27 February 2012

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