Mingzheng Hou
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View article: LDP-Net: An Unsupervised Pansharpening Network Based on Learnable Degradation Processes
LDP-Net: An Unsupervised Pansharpening Network Based on Learnable Degradation Processes Open
Pansharpening in remote sensing image aims at acquiring a high-resolution multispectral (HRMS) image directly by fusing a low-resolution multispectral (LRMS) image with a panchromatic (PAN) image. The main concern is how to effectively com…
View article: Semi‐supervised image super‐resolution with attention CycleGAN
Semi‐supervised image super‐resolution with attention CycleGAN Open
Single‐Image Super‐Resolution (SISR) has always been an important topic in the field of image processing, which attempts to improve the image resolution and is of great significance in practice. Recently, SISR has made substantial progress…
View article: LDP-Net: An Unsupervised Pansharpening Network Based on Learnable Degradation Processes
LDP-Net: An Unsupervised Pansharpening Network Based on Learnable Degradation Processes Open
Pansharpening in remote sensing image aims at acquiring a high-resolution multispectral (HRMS) image directly by fusing a low-resolution multispectral (LRMS) image with a panchromatic (PAN) image. The main concern is how to effectively com…
View article: Attention-Based Octave Network for Hyperspectral Image Denoising
Attention-Based Octave Network for Hyperspectral Image Denoising Open
Inevitable corruption and degeneration make the performance of subsequent high-level semantic tasks in hyperspectral images (HSIs) unsatisfactory. Despite that many denoising methods have been proposed, significant room for improvement sti…
View article: Unsupervised PET Reconstruction from a Bayesian Perspective
Unsupervised PET Reconstruction from a Bayesian Perspective Open
Positron emission tomography (PET) reconstruction has become an ill-posed inverse problem due to low-count projection data, and a robust algorithm is urgently required to improve imaging quality. Recently, the deep image prior (DIP) has dr…
View article: Extreme Low-Resolution Activity Recognition Using a Super-Resolution-Oriented Generative Adversarial Network
Extreme Low-Resolution Activity Recognition Using a Super-Resolution-Oriented Generative Adversarial Network Open
Activity recognition is a fundamental and crucial task in computer vision. Impressive results have been achieved for activity recognition in high-resolution videos, but for extreme low-resolution videos, which capture the action informatio…