L-0-Regularized image downscaling
In this paper, we propose a novel L-0-regularized optimization framework for image downscaling. The optimization is driven by two L-0-regularized priors. The first prior, gradient-ratio prior, is based on the observation that the number of edges in the downscaled image is approximately inverse squar...
Saved in:
Main Authors: | LIU, Junjie, HE, Shengfeng, LAU, Rynson W.H. |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2018
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/7869 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
FLOOD PROJECTION AND ANALYSIS THROUGH STOCHASTIC DOWNSCALING
by: LIU JIANDONG
Published: (2017) -
Variational structure-texture image decomposition on manifolds
by: Wu, X., et al.
Published: (2016) -
A feasible framework to downscale NPP-VIIRS nighttime light imagery using multi-source spatial variables and geographically weighted regression
by: Ye, Yang, et al.
Published: (2022) -
Lightweight salient object detection in optical remote-sensing images via semantic matching and edge alignment
by: Li, Gongyang, et al.
Published: (2023) -
Multiple input multiple output radar three dimensional imaging technique
by: MA CHANGZHENG
Published: (2014)