A remote sensing image fusion algorithm based on Non Subsampled Shearlet Transform coupling detail enhancement factor
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    Abstract:

    In order to overcome the discontinuities and Gibbs phenomenon in many remote sensing image fusion methods, this paper designs an image with Non Sampling Shearlet Transform(NSST) coupling detail enhancement factor by using the gray level and gradient information between pixels fusion method. The intensity(I) component of Multi Spectral(MS) image is separated by Intensity-Hue-Saturation(IHS) transformation. The high and low frequency coefficients of I component and Panchromatic(PAN) image are extracted by NSST. Based on the low-frequency coefficient corresponding to component I, the filling coefficient is calculated by the spatial frequency characteristics of the image. The low-frequency coefficient corresponding to the image is filled into the low-frequency coefficient corresponding to component I, and the low-frequency coefficient is fused. The gray level and gradient information between pixels are utilized to construct detail enhancement factors to measure the differences between pixels and their neighbors, and then the high-frequency coefficients are fused. Based on the fusion coefficient, IHS and NSST inverse transforms are adopted to reconstruct the coefficients, and the fusion results are obtained. The experimental results show that the image fusion algorithm has higher mutual information value, lower spectral deviation value and better spectral and spatial characteristics than the current image fusion algorithm.

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崔怡文,侯德林. Shearlet变换耦合细节强化因子的遥感图像融合算法[J]. Journal of Terahertz Science and Electronic Information Technology ,2020,18(6):1073~1079

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History
  • Received:November 18,2019
  • Revised:January 12,2020
  • Adopted:
  • Online: December 28,2020
  • Published: