Nonlinear image reconstruction in block-based compressive imaging

Jun Ke; Edmund Y. Lam

doi:10.1109/ISCAS.2012.6271926

Nonlinear image reconstruction in block-based compressive imaging

Jun Ke^*, Edmund Y. Lam

^*此作品的通讯作者

The University of Hong Kong

科研成果: 会议稿件 › 论文 › 同行评审

3 引用（Scopus）

摘要

A block-based compressive imaging (BCI) system with sequential architecture is presented in this paper. Feature measurements are collected using the principal component analysis (PCA) projection vectors. Then, we discuss an object prior learning framework based on the Field-of-Expert (FoE) model, and provide its implementation in the BCI reconstruction problem. Experimental results are used to demonstrate the reconstruction performance of the FoE-based method.

源语言	英语
页	2917-2920
页数	4
DOI	https://doi.org/10.1109/ISCAS.2012.6271926
出版状态	已出版 - 2012
已对外发布	是
活动	2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 - Seoul, 韩国期限: 20 5月 2012 → 23 5月 2012

会议

会议	2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012
国家/地区	韩国
市	Seoul
时期	20/05/12 → 23/05/12

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10.1109/ISCAS.2012.6271926

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引用此

@conference{5eaed924360b4f7bb3e853e013836f4c,

title = "Nonlinear image reconstruction in block-based compressive imaging",

abstract = "A block-based compressive imaging (BCI) system with sequential architecture is presented in this paper. Feature measurements are collected using the principal component analysis (PCA) projection vectors. Then, we discuss an object prior learning framework based on the Field-of-Expert (FoE) model, and provide its implementation in the BCI reconstruction problem. Experimental results are used to demonstrate the reconstruction performance of the FoE-based method.",

author = "Jun Ke and Lam, {Edmund Y.}",

year = "2012",

doi = "10.1109/ISCAS.2012.6271926",

language = "English",

pages = "2917--2920",

note = "2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 ; Conference date: 20-05-2012 Through 23-05-2012",

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AU - Ke, Jun

AU - Lam, Edmund Y.

PY - 2012

Y1 - 2012

N2 - A block-based compressive imaging (BCI) system with sequential architecture is presented in this paper. Feature measurements are collected using the principal component analysis (PCA) projection vectors. Then, we discuss an object prior learning framework based on the Field-of-Expert (FoE) model, and provide its implementation in the BCI reconstruction problem. Experimental results are used to demonstrate the reconstruction performance of the FoE-based method.

AB - A block-based compressive imaging (BCI) system with sequential architecture is presented in this paper. Feature measurements are collected using the principal component analysis (PCA) projection vectors. Then, we discuss an object prior learning framework based on the Field-of-Expert (FoE) model, and provide its implementation in the BCI reconstruction problem. Experimental results are used to demonstrate the reconstruction performance of the FoE-based method.

UR - http://www.scopus.com/inward/record.url?scp=84866624413&partnerID=8YFLogxK

U2 - 10.1109/ISCAS.2012.6271926

DO - 10.1109/ISCAS.2012.6271926

M3 - Paper

AN - SCOPUS:84866624413

SP - 2917

EP - 2920

T2 - 2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012

Y2 - 20 May 2012 through 23 May 2012

ER -

Nonlinear image reconstruction in block-based compressive imaging

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