We propose an adaptive regularized algorithm for remote sensing image fusion based on variational methods. In the algorithm, we integrate the inputs using a ＂grey world＂ assumption to achieve visual uniformity. We p...We propose an adaptive regularized algorithm for remote sensing image fusion based on variational methods. In the algorithm, we integrate the inputs using a ＂grey world＂ assumption to achieve visual uniformity. We propose a fusion operator that can automatically select the total variation （TV）-LI term for edges and L2-terms for non-edges. To implement our algorithm, we use the steepest descent method to solve the corresponding Euler-Lagrange equation. Experimental results show that the proposed algorithm achieves remarkable results.展开更多
Pan-sharpening is a method of integrating low-resolution multispectral images with corresponding high-resolution panchromatic images to obtain multispectral images with high spectral and spatial resolution. A novel va...Pan-sharpening is a method of integrating low-resolution multispectral images with corresponding high-resolution panchromatic images to obtain multispectral images with high spectral and spatial resolution. A novel variational model for pan-sharpening is proposed in this paper. The model is mainly based on three hypotheses: 1) the pan-shaipened image can be linearly represented by the corresponding panchromatic image;2) the low-resolution multispectral image is down-sampled from the high-resolution multispectral image through the down-sampling operator;and 3) the satellite image has the low-rank property. Three energy components corresponding to these assumptions are integrated into a variational framework to obtain a total energy function. We adopt the alternating direction method of multipliers (ADMM) to optimize the total energy function. The experimental results show that the proposed method performs better than other mainstream methods in spectral and spatial information preserving aspect.展开更多
基金This work was supported by the National Basic Research Program of China （No. 2011 CB707104） and the National Natural Science Foundation of China （Grant No. 61273298）.
文摘We propose an adaptive regularized algorithm for remote sensing image fusion based on variational methods. In the algorithm, we integrate the inputs using a ＂grey world＂ assumption to achieve visual uniformity. We propose a fusion operator that can automatically select the total variation （TV）-LI term for edges and L2-terms for non-edges. To implement our algorithm, we use the steepest descent method to solve the corresponding Euler-Lagrange equation. Experimental results show that the proposed algorithm achieves remarkable results.
基金the editor and reviewers for their insightful comments and constructive suggestions on the article, and thank Dr. Thomas James Godfrey for helping us to revise the grammar. This work was supported in part by “Chenguang Program” supported by Shanghai Education Development Foundation and Shanghai Municipal Education Commission (Grant No. 17CG25)in part by the Key Project of the National Natural Science Foundation of China (Grant No. 61731009)in part by the National Natural Science Foundation of China (Grant No. 61871185).
文摘Pan-sharpening is a method of integrating low-resolution multispectral images with corresponding high-resolution panchromatic images to obtain multispectral images with high spectral and spatial resolution. A novel variational model for pan-sharpening is proposed in this paper. The model is mainly based on three hypotheses: 1) the pan-shaipened image can be linearly represented by the corresponding panchromatic image;2) the low-resolution multispectral image is down-sampled from the high-resolution multispectral image through the down-sampling operator;and 3) the satellite image has the low-rank property. Three energy components corresponding to these assumptions are integrated into a variational framework to obtain a total energy function. We adopt the alternating direction method of multipliers (ADMM) to optimize the total energy function. The experimental results show that the proposed method performs better than other mainstream methods in spectral and spatial information preserving aspect.
