NDLI: Geometry constrained sparse coding for single image super-resolution

Content Provider	IEEE Xplore Digital Library
Author	Xiaoqiang Lu Haoliang Yuan Pingkun Yan Yuan Yuan Xuelong Li
Copyright Year	2012
Description	Author affiliation: Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, Shaanxi, P. R. China (Xiaoqiang Lu; Haoliang Yuan; Pingkun Yan; Yuan Yuan; Xuelong Li)
Abstract	The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse coding-based image super-resolution. Sparse coding is a typical unsupervised learning method to generate an over-complete dictionary. However, most of the sparse coding methods for image super-resolution fail to simultaneously consider the geometrical structure of the dictionary and corresponding coefficients, which may result in noticeable super-resolution reconstruction artifacts. In this paper, a novel sparse coding method is proposed to preserve the geometrical structure of the dictionary and the sparse coefficients of the data. Moreover, the proposed method can preserve the incoherence of dictionary entries, which is critical for sparse representation. Inspired by the development on non-local self-similarity and manifold learning, the proposed sparse coding method can provide the sparse coefficients and learned dictionary from a new perspective, which have both reconstruction and discrimination properties to enhance the learning performance. Extensive experimental results on image super-resolution have demonstrated the effectiveness of the proposed method.
Starting Page	1648
Ending Page	1655
File Size	300034
Page Count	8
File Format	PDF
ISBN	9781467312264
ISSN	10636919
e-ISBN	9781467312288
e-ISBN	9781467312271
DOI	10.1109/CVPR.2012.6247858
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Encoding Strontium Sparse matrices Image coding Image resolution Vectors
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Image super-resolution by structural sparse coding

Affine-Constrained Group Sparse Coding and Its Application to Image-Based Classifications

Bilevel sparse coding for coupled feature spaces

Centralized sparse representation for image restoration

Image super-resolution based on locality-constrained linear coding

Transfer Sparse Coding for Robust Image Representation

Sparse Coding with a Coupled Dictionary Learning Approach for Textual Image Super-resolution

Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution

Single-Image Super-Resolution Reconstruction via Learned Geometric Dictionaries and Clustered Sparse Coding

Geometry constrained sparse coding for single image super-resolution

Similar Documents

Image super-resolution by structural sparse coding

Affine-Constrained Group Sparse Coding and Its Application to Image-Based Classifications

Bilevel sparse coding for coupled feature spaces

Centralized sparse representation for image restoration

Image super-resolution based on locality-constrained linear coding

Transfer Sparse Coding for Robust Image Representation

Sparse Coding with a Coupled Dictionary Learning Approach for Textual Image Super-resolution

Dictionary Learning and Sparse Coding on Grassmann Manifolds: An Extrinsic Solution

Single-Image Super-Resolution Reconstruction via Learned Geometric Dictionaries and Clustered Sparse Coding

Geometry constrained sparse coding for single image super-resolution