Variational pansharpening by exploiting cartoon-texture similarities
… This enables that the fused high-spatial resolution MS image … texture components from PAN
and MS images. To explore such … -sampled fused MS image is consistent with the MS image, …
and MS images. To explore such … -sampled fused MS image is consistent with the MS image, …
A variational pansharpening method based on gradient sparse representation
… As a result, the spatial quality of the fused MS image can be improved. … fused MS and
LR MS images. By further incorporating a constraint from the estimated HR MS gradients, we …
LR MS images. By further incorporating a constraint from the estimated HR MS gradients, we …
Image fusion meets deep learning: A survey and perspective
… operations on the original MS and PAN images to obtain the … MS image is regarded as the
reference image. In contrast, the unsupervised methods are directly trained on the original MS …
reference image. In contrast, the unsupervised methods are directly trained on the original MS …
MS2DG-Net: Progressive correspondence learning via multiple sparse semantics dynamic graph
… MS^ 2 DG-Net dynamically builds sparse semantics graphs based on sparse semantics …
Extensive experiments prove that MS^ 2 DG-Net outperforms state-of-the-art methods in outlier …
Extensive experiments prove that MS^ 2 DG-Net outperforms state-of-the-art methods in outlier …
A review of multimodal image matching: Methods and applications
Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …
similar structure/content from two or more images that are of significant modalities or …
VP-Net: An interpretable deep network for variational pansharpening
… Considering the spectral difference of various satellite multispectral (MS) imaging platforms,
… a data fidelity term from the low-resolution MS image. Specifically, we build the VP-Net by …
… a data fidelity term from the low-resolution MS image. Specifically, we build the VP-Net by …
Deep learning-based face super-resolution: A survey
… -SSIM) [43] is proposed, which divides the image into multiple windows, first assesses
SSIM for every window separately, and then converges them to obtain MS-SSIM. …
SSIM for every window separately, and then converges them to obtain MS-SSIM. …
Variation-Net: Interpretable variation-inspired deep network for pansharpening
… (PAN) and multispectral (MS) images for a highresolution MS image. We first … MS images
in the real situation is complex and nonlinear, we explore the similarity between PAN and MS …
in the real situation is complex and nonlinear, we explore the similarity between PAN and MS …
Progressive fusion video super-resolution network via exploiting non-local spatio-temporal correlations
… 3DFS needs about 1331 ms. Our model PFS takes about 409 ms to reconstruct one frame …
[38] Zhongyuan Wang, Peng Yi, Kui Jiang, Junjun Jiang, Zhen Han, Tao Lu, and Jiayi Ma. Multi…
[38] Zhongyuan Wang, Peng Yi, Kui Jiang, Junjun Jiang, Zhen Han, Tao Lu, and Jiayi Ma. Multi…
FusionNDVI: A computational fusion approach for high-resolution normalized difference vegetation index
… Especially, we first adopt a large amount of test data, including 165 MS/PAN images from
the Gaofen-1 data set and 142 MS/PAN images from the Gaofen-2 data set, to verify the …
the Gaofen-1 data set and 142 MS/PAN images from the Gaofen-2 data set, to verify the …