PCA-based denoising method for division of focal plane polarimeters

被引：52

作者：

Zhang, Junchao ^{[1
,2
,3
]}

Luo, Haibo ^{[1
,3
,4
]}

Liang, Rongguang ^{[5
]}

Zhou, Wei ^{[6
]}

Hui, Bin ^{[1
,3
,4
]}

Chang, Zheng ^{[1
,3
,4
]}

机构：

[1] Chinese Acad Sci, Shenyang Inst Automat, Shenyang 110016, Peoples R China

[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China

[3] Chinese Acad Sci, Key Lab Opt Elect Informat Proc, Shenyang 110016, Peoples R China

[4] Key Lab Image Understanding & Comp Vis, Shenyang 110016, Peoples R China

[5] Univ Arizona, Ctr Opt Sci, Tucson, AZ 85721 USA

[6] AVIC Jiangxi HONGDU Aviat Ind Grp LTD, Nanchang 220024, Jiangxi, Peoples R China

来源：

OPTICS EXPRESS | 2017年 / 25卷 / 03期

关键词：

IMAGE INTERPOLATION;

D O I：

10.1364/OE.25.002391

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Division of focal plane (DoFP) polarimeters are composed of interlaced linear polarizers overlaid upon a focal plane array sensor. The interpolation is essential to reconstruct polarization information. However, current interpolation methods are based on the unrealistic assumption of noise-free images. Thus, it is advantageous to carry out denoising before interpolation. In this paper, we propose a principle component analysis (PCA) based denoising method, which works directly on DoFP images. Both simulated and real DoFP images are used to evaluate the denoising performance. Experimental results show that the proposed method can effectively suppress noise while preserving edges. (C) 2017 Optical Society of America

引用

页码：2391 / 2400

页数：10

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