Multi-look processing of high-resolution SAS data for improved target detection performance

David P. Williams, Alan J. Hunter

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    12 Scopus citations

    Abstract

    The rich content of synthetic aperture sonar (SAS) data is typically used to generate imagery with resolution as high as theoretically possible. But when the ultimate purpose of the imagery is for detecting objects with sizes large compared to the resolution cell, exploiting the raw data in alternative ways can be more useful. We first show how multiple lower-resolution SAS images (i.e., 'looks') can be obtained in an efficient, principled manner by band-limiting the image wavenumber spectrum of a full-resolution SAS image. By combining these multiple looks (from different aspect and frequency bands), a despeckled image that enjoys greater (target) signal to (seabed) reverberation ratio can be produced. On a large set of real SAS data collected at sea, it is demonstrated how better target detection performance of underwater mines can be achieved by using the lower-resolution despeckled imagery rather than single-look, maximum-resolution imagery.

    Original languageEnglish (US)
    Title of host publication2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
    PublisherIEEE Computer Society
    Pages153-157
    Number of pages5
    ISBN (Electronic)9781479983391
    DOIs
    StatePublished - Dec 9 2015
    EventIEEE International Conference on Image Processing, ICIP 2015 - Quebec City, Canada
    Duration: Sep 27 2015Sep 30 2015

    Publication series

    NameProceedings - International Conference on Image Processing, ICIP
    Volume2015-December
    ISSN (Print)1522-4880

    Other

    OtherIEEE International Conference on Image Processing, ICIP 2015
    Country/TerritoryCanada
    CityQuebec City
    Period9/27/159/30/15

    All Science Journal Classification (ASJC) codes

    • Software
    • Computer Vision and Pattern Recognition
    • Signal Processing

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