Evidence map›Paper›PMID 29937502›Full record

ArticleSensors (Basel, Switzerland)2018

Rectification of Images Distorted by Microlens Array Errors in Plenoptic Cameras.

Suning Li, Yanlong Zhu, Chuanxin Zhang, Yuan Yuan, Heping Tan

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 12 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Suning LiSchool of Energy Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China. 16b902036@stu.hit.edu.cn.
Yanlong ZhuSchool of Energy Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China. 17S002073@stu.hit.edu.cn.
Chuanxin ZhangSchool of Energy Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China. chuanxin@hit.edu.cn.
Yuan YuanSchool of Energy Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China. yuanyuan83@hit.edu.cn.
Heping TanSchool of Energy Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Harbin 150001, China. tanheping@hit.edu.cn.
Harbin Institute of Technology · CNMinistry of Industry and Information Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A plenoptic cameras is a sensor that records the 4D light-field distribution of target scenes. The surface errors of a microlens array (MLA) can cause the degradation and distortion of the raw image captured by a plenoptic camera, resulting in the confusion or loss of light-field information. To address this issue, we propose a method for the local rectification of distorted images using white light-field images. The method consists of microlens center calibration, geometric rectification, and grayscale rectification. The scope of its application to different sized errors and the rectification accuracy of three basic surface errors, including the overall accuracy and the local accuracy, are analyzed through simulation of imaging experiments. The rectified images have a significant improvement in quality, demonstrating the provision of precise light-field data for reconstruction of real objects.

Indexed as

calibrationdistortion rectificationlight-field image processingmicrolens arrayplenoptic camera

Identifiers

PMID29937502
PMCPMC6068943
OpenAlexW2810724426

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.