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Crosstalk Correction for Color Filter Array Image Sensors Based on L(p)-Regularized Multi-Channel Deconvolution
In this paper, we propose a crosstalk correction method for color filter array (CFA) image sensors based on [Formula: see text]-regularized multi-channel deconvolution. Most imaging systems with CFA exhibit a crosstalk phenomenon caused by the physical limitations of the image sensor. In general, th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185327/ https://www.ncbi.nlm.nih.gov/pubmed/35684906 http://dx.doi.org/10.3390/s22114285 |
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author | Kim, Jonghyun Jeong, Kyeonghoon Kang, Moon Gi |
author_facet | Kim, Jonghyun Jeong, Kyeonghoon Kang, Moon Gi |
author_sort | Kim, Jonghyun |
collection | PubMed |
description | In this paper, we propose a crosstalk correction method for color filter array (CFA) image sensors based on [Formula: see text]-regularized multi-channel deconvolution. Most imaging systems with CFA exhibit a crosstalk phenomenon caused by the physical limitations of the image sensor. In general, this phenomenon produces both color degradation and spatial degradation, which are respectively called desaturation and blurring. To improve the color fidelity and the spatial resolution in crosstalk correction, the feasible solution of the ill-posed problem is regularized by image priors. First, the crosstalk problem with complex spatial and spectral degradation is formulated as a multi-channel degradation model. An objective function with a hyper-Laplacian prior is then designed for crosstalk correction. This approach enables the simultaneous improvement of the color fidelity and the sharpness restoration of the details without noise amplification. Furthermore, an efficient solver minimizes the objective function for crosstalk correction consisting of [Formula: see text] regularization terms. The proposed method was verified on synthetic datasets according to various crosstalk and noise levels. Experimental results demonstrated that the proposed method outperforms the conventional methods in terms of the color peak signal-to-noise ratio and structural similarity index measure. |
format | Online Article Text |
id | pubmed-9185327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91853272022-06-11 Crosstalk Correction for Color Filter Array Image Sensors Based on L(p)-Regularized Multi-Channel Deconvolution Kim, Jonghyun Jeong, Kyeonghoon Kang, Moon Gi Sensors (Basel) Article In this paper, we propose a crosstalk correction method for color filter array (CFA) image sensors based on [Formula: see text]-regularized multi-channel deconvolution. Most imaging systems with CFA exhibit a crosstalk phenomenon caused by the physical limitations of the image sensor. In general, this phenomenon produces both color degradation and spatial degradation, which are respectively called desaturation and blurring. To improve the color fidelity and the spatial resolution in crosstalk correction, the feasible solution of the ill-posed problem is regularized by image priors. First, the crosstalk problem with complex spatial and spectral degradation is formulated as a multi-channel degradation model. An objective function with a hyper-Laplacian prior is then designed for crosstalk correction. This approach enables the simultaneous improvement of the color fidelity and the sharpness restoration of the details without noise amplification. Furthermore, an efficient solver minimizes the objective function for crosstalk correction consisting of [Formula: see text] regularization terms. The proposed method was verified on synthetic datasets according to various crosstalk and noise levels. Experimental results demonstrated that the proposed method outperforms the conventional methods in terms of the color peak signal-to-noise ratio and structural similarity index measure. MDPI 2022-06-04 /pmc/articles/PMC9185327/ /pubmed/35684906 http://dx.doi.org/10.3390/s22114285 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kim, Jonghyun Jeong, Kyeonghoon Kang, Moon Gi Crosstalk Correction for Color Filter Array Image Sensors Based on L(p)-Regularized Multi-Channel Deconvolution |
title | Crosstalk Correction for Color Filter Array Image Sensors Based on L(p)-Regularized Multi-Channel Deconvolution |
title_full | Crosstalk Correction for Color Filter Array Image Sensors Based on L(p)-Regularized Multi-Channel Deconvolution |
title_fullStr | Crosstalk Correction for Color Filter Array Image Sensors Based on L(p)-Regularized Multi-Channel Deconvolution |
title_full_unstemmed | Crosstalk Correction for Color Filter Array Image Sensors Based on L(p)-Regularized Multi-Channel Deconvolution |
title_short | Crosstalk Correction for Color Filter Array Image Sensors Based on L(p)-Regularized Multi-Channel Deconvolution |
title_sort | crosstalk correction for color filter array image sensors based on l(p)-regularized multi-channel deconvolution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185327/ https://www.ncbi.nlm.nih.gov/pubmed/35684906 http://dx.doi.org/10.3390/s22114285 |
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