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| MS and PAN Image Fusion Algorithm Based on PST Phase Constraint and Sparse Representation |
| WANG Xianghai1,2, BAI Shifu1, LI Zhi1, SONG Ruoxi2, TAO Jingzhe2 |
1.School of Computer and Information Technology, Liaoning Normal University, Dalian 116081;
2.College of Urban and Environmental Sciences, Liaoning Normal Universtiy, Dalian 116029 |
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Abstract In the remote sensing image fusion based on multi-spectral(MS) image and panchromatic(PAN) image, effective extracting the texture feature information of PAN and injecting targeted information into MS image are crucial to the high quality of image fusion. Therefore, the MS and PAN image pansharpening algorithm based on phase constraint of phase stretch transform(PST) and sparse representation is proposed in this paper. Firstly, the MS and PAN images are filtered by Gaussian filter. For the low and medium frequency information, the fusion weight constraint is obtained by the phase difference of high frequency based on the sensitivity of the PST phase difference to the edge and texture region in the image. For the high frequency information, a training dictionary is obtained by learning the high frequency information of the PAN image, and the dictionary is used to sparsely represent and fuse the high frequency information of MS and PAN images, therefore the accuracy of high frequency fusion is improved. The proposed algorithm overcomes the poor fusion effect of traditional fusion methods on the edge texture region and the distortion of spectral information, achieves better fusion result. A large number of simulation experiments verify the effectiveness of the proposed method.
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Received: 10 September 2018
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| Fund:Supported by National Natural Science Foundation of China(No.41671439,61402214), Program for Liaoning Innovation Research Team in University(No.LT2017013) |
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Corresponding Authors:
(WANG Xianghai(Corresponding author), Ph.D., professor. His research interests include remote sensing image processing and multimedia information processing.)
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| About author:: (BAI Shifu, master student. His research interests include remote sensing image processing.)(LI Zhi, master student. His research inte-rests include image segmentation and remote sensing image fusion.)(SONG Ruoxi, Ph.D. candidate. Her research interests include remote sensing image processing and mathematical modeling.)(TAO Jingzhe, Ph.D. candidate. His research interests include remote sensing fusion and super-resolution reconstruction.) |
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2019, Vol. 32 
