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Spectral remapping for image downscaling
ACM Transactions on Graphics, 2017We present an image downscaling technique capable of appropriately representing high-frequency structured patterns. Our method breaks conventional wisdom in sampling theory---instead of discarding high-frequency information to avoid aliasing, it controls aliasing by remapping such information to the representable range of the downsampled spectrum.
Eduardo S. L. Gastal, Manuel M. Oliveira
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Assessment of Various Statistical Downscaling Methods for Downscaling Precipitation in Florida
World Environmental and Water Resources Congress 2013, 2013Several statistical downscaling models have been developed in the past couple of decades to assess the hydrologic impacts of climate change by projecting the station-scale hydrological variables from large-scale atmospheric variables simulated by General Circulation Models (GCMs).
Aneesh Goly, Ramesh S. V. Teegavarapu
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Thermal Aspects of Satellite Downscaling
Journal of Thermophysics and Heat Transfer, 2009The strong trend toward nanosatellites creates new challenges in terms of thermal balance control. The thermal balance of a satellite is determined by the heat dissipation in its subsystems and by the thermal connections between them. As satellites become smaller, heat dissipation in their subsystems tends to decrease and thermal connectivity scales ...
van Weeren, H. +4 more
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2018
Image downscaling is one of the most classical problems in computer vision that aims to preserve the visual appearance of the original image when it is resized to a smaller scale. Upscaling a small image back to its original size is a difficult and ill-posed problem due to information loss that arises in the downscaling process.
Heewon Kim +3 more
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Image downscaling is one of the most classical problems in computer vision that aims to preserve the visual appearance of the original image when it is resized to a smaller scale. Upscaling a small image back to its original size is a difficult and ill-posed problem due to information loss that arises in the downscaling process.
Heewon Kim +3 more
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Bivariate Downscaling With Asynchronous Measurements
Journal of Agricultural, Biological, and Environmental Statistics, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
He, Xuming, Yang, Yunwen, Zhang, Jingfei
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2017
Downscaling in Weather Forecasting The first downscaling methods had been invented already in the late 1940s (Klein 1948) and became operational in the early days of numerical weather prediction at the end of the 1950s. Back then, operational numerical weather prediction models were by far too coarse to predict local weather, and furthermore they did
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Downscaling in Weather Forecasting The first downscaling methods had been invented already in the late 1940s (Klein 1948) and became operational in the early days of numerical weather prediction at the end of the 1950s. Back then, operational numerical weather prediction models were by far too coarse to predict local weather, and furthermore they did
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Content-adaptive image downscaling
ACM Transactions on Graphics, 2013This paper introduces a novel content-adaptive image downscaling method. The key idea is to optimize the shape and locations of the downsampling kernels to better align with local image features. Our content-adaptive kernels are formed as a bilateral combination of two Gaussian kernels defined over space and color ...
Johannes Kopf 0001 +2 more
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Downscaling of environmental indicators: A review
Science of The Total EnvironmentEnvironmental indicators at different scales are important for environmental management, daily life, and scientific research. Because of the lack of statistics below a national scale for many environmental indicators, scholars have developed various downscaling methods to obtain finer-scale and diverse forms of data for different environmental ...
Shiting, Li +6 more
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Impact of Downscaling on Adversarial Images
2022 IEEE International Conference on Image Processing (ICIP), 2022Benoît Bonnet 0001 +2 more
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