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Image super-resolution: The techniques, applications, and future
Super-resolution (SR) technique reconstructs a higher-resolution image or sequence from
the observed LR images. As SR has been developed for more than three decades, both …
the observed LR images. As SR has been developed for more than three decades, both …
Super-resolution: a comprehensive survey
Super-resolution, the process of obtaining one or more high-resolution images from one or
more low-resolution observations, has been a very attractive research topic over the last two …
more low-resolution observations, has been a very attractive research topic over the last two …
Boosting the accuracy of multispectral image pansharpening by learning a deep residual network
In the field of multispectral (MS) and panchromatic image fusion (pansharpening), the
impressive effectiveness of deep neural networks has recently been employed to overcome …
impressive effectiveness of deep neural networks has recently been employed to overcome …
Hyperspectral image denoising employing a spectral–spatial adaptive total variation model
The amount of noise included in a hyperspectral image limits its application and has a
negative impact on hyperspectral image classification, unmixing, target detection, and so on …
negative impact on hyperspectral image classification, unmixing, target detection, and so on …
Learning multiple linear map**s for efficient single image super-resolution
Example learning-based superresolution (SR) algorithms show promise for restoring a high-
resolution (HR) image from a single low-resolution (LR) input. The most popular …
resolution (HR) image from a single low-resolution (LR) input. The most popular …
Utility-driven adaptive preprocessing for screen content video compression
In this work, we propose a utility-driven preprocessing technique for high-efficiency screen
content video (SCV) compression based on the temporal masking effect, which was found to …
content video (SCV) compression based on the temporal masking effect, which was found to …
Multiframe super-resolution employing a spatially weighted total variation model
Total variation (TV) has been used as a popular and effective image prior model in
regularization-based image processing fields, such as denoising, deblurring, super …
regularization-based image processing fields, such as denoising, deblurring, super …
A super-resolution reconstruction algorithm for hyperspectral images
The spatial resolution of a hyperspectral image is often coarse because of the limitations of
the imaging hardware. Super-resolution reconstruction (SRR) is a promising signal post …
the imaging hardware. Super-resolution reconstruction (SRR) is a promising signal post …
Adjustable model-based fusion method for multispectral and panchromatic images
In this paper, an adjustable model-based image fusion method for multispectral (MS) and
panchromatic (PAN) images is developed. The relationships of the desired high spatial …
panchromatic (PAN) images is developed. The relationships of the desired high spatial …
Inpainting for remotely sensed images with a multichannel nonlocal total variation model
Filling dead pixels or removing uninteresting objects is often desired in the applications of
remotely sensed images. In this paper, an effective image inpainting technology is …
remotely sensed images. In this paper, an effective image inpainting technology is …