Image Processing
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
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180 Views
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
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30 Views
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
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46 Views
To test the feasibility of the idea: Using the processed data of sentinel-2 and GlobeLand30 as the input image and ground truth of subspace clustering for land cover classification, a dataset named 'MSI_Gwadar' is created.
'MSI_Gwadar' is a multi-spectral remote sensing image of Gwadar (town and seaport, southwestern Pakistan) and its four regions of interest, which includes MATLAB data files and ground truth files of the study area and its four regions of interest.
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267 Views
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
- Categories:
28 Views
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
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34 Views
The results are based on the measurements conducted on small drones and a bionic bird using a 60 GHz millimeter wave radar, analyzing their micro-Doppler characteristics in both time and frequency domain. The results are presented in .pkl format. The more detailed description of the data and how the authors processed it will be updated soon.
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1067 Views
VSR-QAD-3Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
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43 Views
The dataset is a validation dataset for low-light image enhancement and noise reduction tasks. The dataset contains triples of images: low-light images, target images and low-light enhanced images. We used this dataset to generate results for the manuscript "Adaptive Guided Upsampling for Low-light Image Enhancement" submitted to IEEE ACCESS for review. The dataset allows other researchers to work our material.
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54 Views
Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models are crucially important both for advancing video SR algorithms and for viewing quality assurance. Therefore, we establish a super-resolution video quality assessment database （VSR-QAD） for implementing super-resolution video quality assessment.
- Categories:
37 Views