Energy-driven image interpolation using Gaussian process regression

DOI10.1155/2012/435924zbMath1251.94011OpenAlexW2045448913WikidataQ58905886 ScholiaQ58905886MaRDI QIDQ1760690

Lingling Zi, Junping Du

Publication date: 15 November 2012

Published in: Journal of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2012/435924

zbMATH Keywords

image processingimage interpolationhigh-resolution imageslow-resolution images

Mathematics Subject Classification ID

Theory of statistical experiments (62B15) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

• Asymptotic behavior of the likelihood function of covariance matrices of spatial Gaussian processes
• Efficient indexing of interval time sequences
• Smooth local interpolation of surfaces using normal vectors
• An Adaptable $k$-Nearest Neighbors Algorithm for MMSE Image Interpolation
• Online Sparse Gaussian Process Regression and Its Applications
• Gradient Profile Prior and Its Applications in Image Super-Resolution and Enhancement
• Real-Time Artifact-Free Image Upscaling
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