Learning Local Distribution for Extremely Efficient Single-Image Super-Resolution

Learning Local Distribution for Extremely Efficient Single-Image Super-Resolution

Achieving balance between efficiency and performance is a key problem for convolution neural network (CNN)-based single-image super-resolution (SISR) algorithms. Existing methods tend to directly output high-resolution (HR) pixels or residuals to reconstruct the HR image and focus a lot of attention...

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Bibliographic Details
Main Authors: Wei Wu, Wen Xu, Bolun Zheng, Aiai Huang, Chenggang Yan
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Electronics
Subjects:
image super-resolution
local distribution model
extreme efficient
multi-layer neural network
Online Access:https://www.mdpi.com/2079-9292/11/9/1348

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