A hybrid method for multi-sensor remote sensing image registration based on salience region

Jichao Jiao, Zhongliang Deng, Baojun Zhao, John Femiani, Xin Wang

    Research output: Contribution to journalArticle

    4 Scopus citations

    Abstract

    In order to align the remote sensing images, we propose a novel hybrid method that combines image segmentation and salient region detection, which is inspired by human vision system. First of all, we present a novel superpixel-based method for dividing the image into sub-areas. Second, we propose a novel method based on color and image textures for detecting salient regions composed by superpixels. Then, we extract a new feature based on difference of Gaussian and local binary pattern from the salient regions. Finally, the sensed image is transformed by thin-plate spline. The proposed algorithm was tested on 30 pairs of remote sensing images and compared to other three state of the art methods. Experimental results show our approach is fast and robust, while still being efficient, which is better than other three methods.

    Original languageEnglish (US)
    Pages (from-to)2293-2317
    Number of pages25
    JournalCircuits, Systems, and Signal Processing
    Volume33
    Issue number7
    DOIs
    StatePublished - Jul 2014

    Keywords

    • Human vision system
    • Image registration
    • Image segmentation
    • Local binary pattern
    • Remote sensing images
    • Salient region detection

    ASJC Scopus subject areas

    • Signal Processing
    • Applied Mathematics

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