17 April 2018 Multitask saliency detection model for synthetic aperture radar (SAR) image and its application in SAR and optical image fusion
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Abstract
Saliency detection in synthetic aperture radar (SAR) images is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR images. We extract four features of the SAR image, which include the intensity, orientation, uniqueness, and global contrast, as the input of the MSD model. The saliency map is generated by the multitask sparsity pursuit, which integrates the multiple features collaboratively. Detection of different scale features is also taken into consideration. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps obtained by the MSD model, we apply the saliency map of the SAR image to the SAR and color optical image fusion. The experimental results of real data show that the saliency map obtained by the MSD model helps to improve the fusion effect, and the salient areas in the SAR image can be highlighted in the fusion results.
© 2018 SPIE and IS&T
Chunhui Liu, Chunhui Liu, Duona Zhang, Duona Zhang, Xintao Zhao, Xintao Zhao, } "Multitask saliency detection model for synthetic aperture radar (SAR) image and its application in SAR and optical image fusion," Journal of Electronic Imaging 27(2), 023026 (17 April 2018). https://doi.org/10.1117/1.JEI.27.2.023026 . Submission: Received: 7 December 2017; Accepted: 27 March 2018
Received: 7 December 2017; Accepted: 27 March 2018; Published: 17 April 2018
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