Collaborative and compressive high-resolution imaging

Yanning Zhang, Haichao Zhang, Thomas S Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a novel collaborative and compressive high-resolution image acquisition method in this paper. The proposed approach acquires several coded low resolution observations via the designed image formation process. The imaging process is achieved via random convolution followed with subsampling, which is practical for hardware implementation. The latent high resolution image is recovered via a joint optimization scheme in a collaborative manner. An efficient optimization algorithm is developed for recovering the latent high-resolution image. Experimental results compared with several related imaging schemes have clearly demonstrated the effectiveness of the propose method.

Original languageEnglish (US)
Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
Pages3062-3065
Number of pages4
StatePublished - Dec 1 2012
Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
Duration: Nov 11 2012Nov 15 2012

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Other

Other21st International Conference on Pattern Recognition, ICPR 2012
Country/TerritoryJapan
CityTsukuba
Period11/11/1211/15/12

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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