Fast and Stable Hyperspectral Multispectral Image Fusion Technique Using Moore–Penrose Inverse Solver

Fusion low-resolution hyperspectral images (LR-HSI) and high-resolution multispectral images (HR-MSI) are important methods for obtaining high-resolution hyperspectral images (HR-HSI). Some hyperspectral image fusion application areas have strong real-time requirements for image fusion, and a fast fusion method is urgently needed. This paper proposes a fast and stable fusion method (FSF) based on matrix factorization, which can largely reduce the computational workloads of image fusion to achieve fast and efficient image fusion. FSF introduces the Moore–Penrose inverse in the fusion model to simplify the estimation of the coefficient matrix and uses singular value decomposition (SVD) to simplify the estimation of the spectral basis, thus significantly reducing the computational effort of model solving. Meanwhile, FSF introduces two multiplicative iterative processes to optimize the spectral basis and coefficient matrix to achieve stable and high-quality fusion. We have tested the fusion method on remote sensing and ground-based datasets. The experiments show that our proposed method can achieve the performance of several state-of-the-art algorithms while reducing execution time to less than 1% of such algorithms.

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Hyperspectral image fusion method based on second generation wavelet

10.1117/12.750426 ◽

2007 ◽

Author(s):

Kecheng Wang ◽

Jie Yang ◽

Zhefei Hou ◽

Yu Liu

Keyword(s):

Image Fusion ◽

Second Generation ◽

Hyperspectral Image ◽

Fusion Method ◽

Hyperspectral Image Fusion ◽

Second Generation Wavelet ◽

Image Fusion Method

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Seamless Mosaicking of UAV-Based Push-Broom Hyperspectral Images for Environment Monitoring

Remote Sensing ◽

10.3390/rs13224720 ◽

2021 ◽

Vol 13 (22) ◽

pp. 4720

Author(s):

Lina Yi ◽

Jing M. Chen ◽

Guifeng Zhang ◽

Xiao Xu ◽

Xing Ming ◽

...

Keyword(s):

Image Registration ◽

Image Fusion ◽

Hyperspectral Image ◽

Weighted Average ◽

Phase Correlation ◽

Hyperspectral Images ◽

Alternative Methods ◽

Fusion Method ◽

Environment Monitoring ◽

Geometrical Accuracy

This paper proposes a systematic image mosaicking methodology to produce hyperspectral image for environment monitoring using an emerging UAV-based push-broom hyperspectral imager. The suitability of alternative methods in each step is assessed by experiments of an urban scape, a river course and a forest study area. First, the hyperspectral image strips were acquired by sequentially stitching the UAV images acquired by push-broom scanning along each flight line. Next, direct geo-referencing was applied to each image strip to get initial geo-rectified result. Then, with ground control points, the curved surface spline function was used to transform the initial geo-rectified image strips to improve their geometrical accuracy. To further remove the displacement between pairs of image strips, an improved phase correlation (IPC) and a SIFT and RANSAC-based method (SR) were used in image registration. Finally, the weighted average and the best stitching image fusion method were used to remove the spectral differences between image strips and get the seamless mosaic. Experiment results showed that as the GCPs‘ number increases, the mosaicked image‘s geometrical accuracy increases. In image registration, there exists obvious edge information that can be accurately extracted from the urban scape and river course area; comparative results can be achieved by the IPC method with less time cost. However, for the ground objects with complex texture like forest, the edges extracted from the image is prone to be inaccurate and result in the failure of the IPC method, and only the SR method can get a good result. In image fusion, the best stitching fusion method can get seamless results for all three study areas. Whereas, the weighted average fusion method was only useful in eliminating the stitching line for the river course and forest areas but failed for the urban scape area due to the spectral heterogeneity of different ground objects. For different environment monitoring applications, the proposed methodology provides a practical solution to seamlessly mosaic UAV-based push-broom hyperspectral images with high geometrical accuracy and spectral fidelity.

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