Cargando…
Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack
Due to the complex angular-spatial structure, light field (LF) image processing faces more opportunities and challenges than ordinary image processing. The angular-spatial structure loss of LF images can be reflected from their various representations. The angular and spatial information penetrate e...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810542/ https://www.ncbi.nlm.nih.gov/pubmed/35126077 http://dx.doi.org/10.3389/fncom.2021.768021 |
_version_ | 1784644277809184768 |
---|---|
author | Meng, Chunli An, Ping Huang, Xinpeng Yang, Chao Chen, Yilei |
author_facet | Meng, Chunli An, Ping Huang, Xinpeng Yang, Chao Chen, Yilei |
author_sort | Meng, Chunli |
collection | PubMed |
description | Due to the complex angular-spatial structure, light field (LF) image processing faces more opportunities and challenges than ordinary image processing. The angular-spatial structure loss of LF images can be reflected from their various representations. The angular and spatial information penetrate each other, so it is necessary to extract appropriate features to analyze the angular-spatial structure loss of distorted LF images. In this paper, a LF image quality evaluation model, namely MPFS, is proposed based on the prediction of global angular-spatial distortion of macro-pixels and the evaluation of local angular-spatial quality of the focus stack. Specifically, the angular distortion of the LF image is first evaluated through the luminance and chrominance of macro-pixels. Then, we use the saliency of spatial texture structure to pool an array of predicted values of angular distortion to obtain the predicted value of global distortion. Secondly, the local angular-spatial quality of the LF image is analyzed through the principal components of the focus stack. The focalizing structure damage caused by the angular-spatial distortion is calculated using the features of corner and texture structures. Finally, the global and local angular-spatial quality evaluation models are combined to realize the evaluation of the overall quality of the LF image. Extensive comparative experiments show that the proposed method has high efficiency and precision. |
format | Online Article Text |
id | pubmed-8810542 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88105422022-02-04 Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack Meng, Chunli An, Ping Huang, Xinpeng Yang, Chao Chen, Yilei Front Comput Neurosci Neuroscience Due to the complex angular-spatial structure, light field (LF) image processing faces more opportunities and challenges than ordinary image processing. The angular-spatial structure loss of LF images can be reflected from their various representations. The angular and spatial information penetrate each other, so it is necessary to extract appropriate features to analyze the angular-spatial structure loss of distorted LF images. In this paper, a LF image quality evaluation model, namely MPFS, is proposed based on the prediction of global angular-spatial distortion of macro-pixels and the evaluation of local angular-spatial quality of the focus stack. Specifically, the angular distortion of the LF image is first evaluated through the luminance and chrominance of macro-pixels. Then, we use the saliency of spatial texture structure to pool an array of predicted values of angular distortion to obtain the predicted value of global distortion. Secondly, the local angular-spatial quality of the LF image is analyzed through the principal components of the focus stack. The focalizing structure damage caused by the angular-spatial distortion is calculated using the features of corner and texture structures. Finally, the global and local angular-spatial quality evaluation models are combined to realize the evaluation of the overall quality of the LF image. Extensive comparative experiments show that the proposed method has high efficiency and precision. Frontiers Media S.A. 2022-01-20 /pmc/articles/PMC8810542/ /pubmed/35126077 http://dx.doi.org/10.3389/fncom.2021.768021 Text en Copyright © 2022 Meng, An, Huang, Yang and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Meng, Chunli An, Ping Huang, Xinpeng Yang, Chao Chen, Yilei Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack |
title | Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack |
title_full | Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack |
title_fullStr | Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack |
title_full_unstemmed | Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack |
title_short | Image Quality Evaluation of Light Field Image Based on Macro-Pixels and Focus Stack |
title_sort | image quality evaluation of light field image based on macro-pixels and focus stack |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810542/ https://www.ncbi.nlm.nih.gov/pubmed/35126077 http://dx.doi.org/10.3389/fncom.2021.768021 |
work_keys_str_mv | AT mengchunli imagequalityevaluationoflightfieldimagebasedonmacropixelsandfocusstack AT anping imagequalityevaluationoflightfieldimagebasedonmacropixelsandfocusstack AT huangxinpeng imagequalityevaluationoflightfieldimagebasedonmacropixelsandfocusstack AT yangchao imagequalityevaluationoflightfieldimagebasedonmacropixelsandfocusstack AT chenyilei imagequalityevaluationoflightfieldimagebasedonmacropixelsandfocusstack |