Selective Image Super-Resolution

10/27/2010
by   Ju Sun, et al.
0

In this paper we propose a vision system that performs image Super Resolution (SR) with selectivity. Conventional SR techniques, either by multi-image fusion or example-based construction, have failed to capitalize on the intrinsic structural and semantic context in the image, and performed "blind" resolution recovery to the entire image area. By comparison, we advocate example-based selective SR whereby selectivity is exemplified in three aspects: region selectivity (SR only at object regions), source selectivity (object SR with trained object dictionaries), and refinement selectivity (object boundaries refinement using matting). The proposed system takes over-segmented low-resolution images as inputs, assimilates recent learning techniques of sparse coding (SC) and grouped multi-task lasso (GMTL), and leads eventually to a framework for joint figure-ground separation and interest object SR. The efficiency of our framework is manifested in our experiments with subsets of the VOC2009 and MSRC datasets. We also demonstrate several interesting vision applications that can build on our system.

READ FULL TEXT

page 3

page 9

page 14

page 17

research
08/03/2019

CRNet: Image Super-Resolution Using A Convolutional Sparse Coding Inspired Network

Convolutional Sparse Coding (CSC) has been attracting more and more atte...
research
03/30/2018

Task-Driven Super Resolution: Object Detection in Low-resolution Images

We consider how image super resolution (SR) can contribute to an object ...
research
07/26/2017

Structure-Preserving Image Super-resolution via Contextualized Multi-task Learning

Single image super resolution (SR), which refers to reconstruct a higher...
research
10/12/2021

Deep Fusion Prior for Multi-Focus Image Super Resolution Fusion

This paper unifies the multi-focus images fusion (MFIF) and blind super ...
research
07/07/2021

Blind Image Super-Resolution: A Survey and Beyond

Blind image super-resolution (SR), aiming to super-resolve low-resolutio...
research
02/07/2018

Super-resolution of spatiotemporal event-based image

Super-resolution (SR) is a useful technology to generate a high-resoluti...
research
06/25/2020

Deep Learning for Cornea Microscopy Blind Deblurring

The goal of this project is to build a deep-learning solution that deblu...

Please sign up or login with your details

Forgot password? Click here to reset