Multitask Saliency Detection model for SAR Image and Its Application in SAR and Optical Image Fusion

Saliency detection in synthetic aperture radar (SAR) image is a difficult problem. This paper proposed a multitask saliency detection (MSD) model for the saliency detection task of SAR image. Firstly, we extract four features of SAR image as the input of the MSD model, which include the intensity, orientation, uniqueness and global contrast. Then, the saliency map is generated by the multitask sparsity pursuit (MTSP) which integrates the multiple features collaboratively. Subjective and objective evaluation of the MSD model verifies its effectiveness. Based on the saliency maps of the source images, an image fusion method is proposed for the SAR and color optical image fusion. The experimental results of real data show the proposed image fusion method is superior to the presenting methods in terms of several universal quality evaluation indexes, as well as in the visual quality. The salient areas in the SAR image can be highlighted and the spatial and spectral details of color optical image can also be preserved in the fusion result.

[1]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[2]  Hassan Ghassemian,et al.  Combining the spectral PCA and spatial PCA fusion methods by an optimal filter , 2016, Inf. Fusion.

[3]  Guangluan Xu,et al.  Aircraft recognition in high resolution SAR images using saliency map and scattering structure features , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[4]  Shigang Wang,et al.  New Hierarchical Saliency Filtering for Fast Ship Detection in High-Resolution SAR Images , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[5]  Shanshan Chen,et al.  Saliency Detector for SAR Images Based on Pattern Recurrence , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[6]  B. Schölkopf,et al.  Graph-Based Visual Saliency , 2007 .

[7]  Yue Qi,et al.  Airborne SAR and optical image fusion based on IHS transform and joint non-negative sparse representation , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[8]  Luciano Alparone,et al.  A global quality measurement of pan-sharpened multispectral imagery , 2004, IEEE Geoscience and Remote Sensing Letters.

[9]  Myungjin Choi,et al.  A new intensity-hue-saturation fusion approach to image fusion with a tradeoff parameter , 2006, IEEE Trans. Geosci. Remote. Sens..

[10]  Liqing Zhang,et al.  Saliency Detection: A Spectral Residual Approach , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Nannan Yu,et al.  Image Features Extraction and Fusion Based on Joint Sparse Representation , 2011, IEEE Journal of Selected Topics in Signal Processing.

[12]  Xiaolin Tian,et al.  SAR image despeckling by combining saliency map and threshold selection , 2013 .

[13]  Olaf Hellwich,et al.  Saliency and salient region detection in SAR polarimetry , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[14]  Mehdi Amoon,et al.  New method for ship detection in synthetic aperture radar imagery based on the human visual attention system , 2013 .

[15]  Gemma Piella,et al.  Image Fusion for Enhanced Visualization: A Variational Approach , 2009, International Journal of Computer Vision.

[16]  Huang Hai-dong.  A New Method for Remote Sensing Image Fusion Based on Nonsubsampled Contourlet Transform , 2008 .

[17]  Michael Möller,et al.  An Adaptive IHS Pan-Sharpening Method , 2010, IEEE Geoscience and Remote Sensing Letters.

[18]  Joel Spruck,et al.  A variational approach to image fusion , 2000 .

[19]  Wang Chao.  Multi-focus image fusion with salience preserving , 2008 .

[20]  Chun-Liang Chien,et al.  Image Fusion With No Gamut Problem by Improved Nonlinear IHS Transforms for Remote Sensing , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[21]  Yan Wang,et al.  Infrared and multi-type images fusion algorithm based on contrast pyramid transform , 2016 .

[22]  Jian Yu,et al.  Saliency Detection by Multitask Sparsity Pursuit , 2012, IEEE Transactions on Image Processing.

[23]  Gui Gao,et al.  A Parzen-Window-Kernel-Based CFAR Algorithm for Ship Detection in SAR Images , 2011, IEEE Geoscience and Remote Sensing Letters.

[24]  Liming Zhang,et al.  Spatio-temporal Saliency detection using phase spectrum of quaternion fourier transform , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[25]  Xiaojing Huang,et al.  Saliency detection based on distance between patches in polarimetric SAR images , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.

[26]  Youkyung Han,et al.  An Area-Based Image Fusion Scheme for the Integration of SAR and Optical Satellite Imagery , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[27]  KochChristof,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 1998 .

[28]  Yi Su,et al.  Fast and Accurate Target Detection Based on Multiscale Saliency and Active Contour Model for High-Resolution SAR Images , 2016, IEEE Transactions on Geoscience and Remote Sensing.

[29]  Jocelyn Chanussot,et al.  Indusion: Fusion of Multispectral and Panchromatic Images Using the Induction Scaling Technique , 2008, IEEE Geoscience and Remote Sensing Letters.

[30]  Lihi Zelnik-Manor,et al.  Context-Aware Saliency Detection , 2012, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Ying Yu,et al.  Hebbian-based neural networks for bottom-up visual attention and its applications to ship detection in SAR images , 2011, Neurocomputing.