HKUST Library Institutional Repository Banner

HKUST Institutional Repository >
Computer Science and Engineering >
CSE Conference Papers >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/7465
Title: Image hallucination using neighbor embedding over visual primitive manifolds
Authors: Yeung, Dit-Yan
Fan, Wei
Keywords: Image reconstruction
Image resolution
Geometry
Learning systems
Manifolds
Issue Date: Jun-2007
Citation: Proceedings 2007 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, 17-22 June 2007, Minneapolis, MN, USA, p. 1-7
Abstract: In this paper, we propose a novel learning-based method for image hallucination, with image super-resolution being a specific application that we focus on here. Given a low-resolution image, its underlying higher-resolution details are synthesized based on a set of training images. In order to build a compact yet descriptive training set, we investigate the characteristic local structures contained in large volumes of small image patches. Inspired by recent progress in manifold learning research, we take the assumption that small image patches in the low-resolution and high-resolution images form manifolds with similar local geometry in the corresponding image feature spaces. This assumption leads to a super-resolution approach which reconstructs the feature vector corresponding to an image patch by its neighbors in the feature space. In addition, the residual errors associated with the reconstructed image patches are also estimated to compensate for the information loss in the local averaging process. Experimental results show that our hallucination method can synthesize higher-quality images compared with other methods.
Rights: © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
URI: http://hdl.handle.net/1783.1/7465
Appears in Collections:CSE Conference Papers

Files in This Item:

File Description SizeFormat
yeung.cvpr20071.pdfpre-published version7409KbAdobe PDFView/Open

All items in this Repository are protected by copyright, with all rights reserved.