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Estimation and Sharpening of Blur in Degraded Images Captured by a Camera on a Moving Object

In this research, we aim to propose an image sharpening method to make it easy to identify concrete cracks from blurred images captured by a moving camera. This study is expected to help realize social infrastructure maintenance using a wide range of robotic technologies, and to solve the future lab...

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Autores principales: Hayashi, Toshiyuki, Tsubouchi, Takashi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877064/
https://www.ncbi.nlm.nih.gov/pubmed/35214538
http://dx.doi.org/10.3390/s22041635
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author Hayashi, Toshiyuki
Tsubouchi, Takashi
author_facet Hayashi, Toshiyuki
Tsubouchi, Takashi
author_sort Hayashi, Toshiyuki
collection PubMed
description In this research, we aim to propose an image sharpening method to make it easy to identify concrete cracks from blurred images captured by a moving camera. This study is expected to help realize social infrastructure maintenance using a wide range of robotic technologies, and to solve the future labor shortage and shortage of engineers. In this paper, a method to estimate parameters of motion blur for Point Spread Function (PSF) is mainly discussed, where we assume that there are two main degradation factors caused by the camera, out-of-focus blur and motion blur. A major contribution of this paper is that the parameters can properly be estimated from a sub-image of the object under inspection if the sub-image contains uniform speckled texture. Here, the cepstrum of the sub-image is fully utilized. Then, a filter convoluted PSF which consists of convolution with PSF (motion blur) and PSF (out-of focus blur) can be utilized for deconvolution of the blurred image for sharpening with significant effect. PSF (out-of-focus blur) is a constant function unique to each camera and lens, and can be confirmed before or after shooting. PSF (motion blur), on the other hand, needs to be estimated on a case-by-case basis since the amount and direction of camera movement varies depending on the time of shooting. Previous research papers have sometimes encountered difficulties in estimating the parameters of motion blur because of the emphasis on generality. In this paper, the main object is made of concrete, and on the surface of it there are speckled textures. We hypothesized that we can narrow down the candidates of parameters of motion blur by using these speckled patterns. To verify this hypothesis, we conducted experiments to confirm and examine the following two points using a general-purpose camera used in actual bridge inspections: 1. Influence on the cepstrum when the isolated point-like texture unique to concrete structures is used as a feature point. 2. Selection method of multiple images to narrow down the candidate minima of the cepstrum. It is novel that the parameters of motion blur can be well estimated by using the unique speckled pattern on the surface of the object.
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spelling pubmed-88770642022-02-26 Estimation and Sharpening of Blur in Degraded Images Captured by a Camera on a Moving Object Hayashi, Toshiyuki Tsubouchi, Takashi Sensors (Basel) Article In this research, we aim to propose an image sharpening method to make it easy to identify concrete cracks from blurred images captured by a moving camera. This study is expected to help realize social infrastructure maintenance using a wide range of robotic technologies, and to solve the future labor shortage and shortage of engineers. In this paper, a method to estimate parameters of motion blur for Point Spread Function (PSF) is mainly discussed, where we assume that there are two main degradation factors caused by the camera, out-of-focus blur and motion blur. A major contribution of this paper is that the parameters can properly be estimated from a sub-image of the object under inspection if the sub-image contains uniform speckled texture. Here, the cepstrum of the sub-image is fully utilized. Then, a filter convoluted PSF which consists of convolution with PSF (motion blur) and PSF (out-of focus blur) can be utilized for deconvolution of the blurred image for sharpening with significant effect. PSF (out-of-focus blur) is a constant function unique to each camera and lens, and can be confirmed before or after shooting. PSF (motion blur), on the other hand, needs to be estimated on a case-by-case basis since the amount and direction of camera movement varies depending on the time of shooting. Previous research papers have sometimes encountered difficulties in estimating the parameters of motion blur because of the emphasis on generality. In this paper, the main object is made of concrete, and on the surface of it there are speckled textures. We hypothesized that we can narrow down the candidates of parameters of motion blur by using these speckled patterns. To verify this hypothesis, we conducted experiments to confirm and examine the following two points using a general-purpose camera used in actual bridge inspections: 1. Influence on the cepstrum when the isolated point-like texture unique to concrete structures is used as a feature point. 2. Selection method of multiple images to narrow down the candidate minima of the cepstrum. It is novel that the parameters of motion blur can be well estimated by using the unique speckled pattern on the surface of the object. MDPI 2022-02-19 /pmc/articles/PMC8877064/ /pubmed/35214538 http://dx.doi.org/10.3390/s22041635 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
Hayashi, Toshiyuki
Tsubouchi, Takashi
Estimation and Sharpening of Blur in Degraded Images Captured by a Camera on a Moving Object
title Estimation and Sharpening of Blur in Degraded Images Captured by a Camera on a Moving Object
title_full Estimation and Sharpening of Blur in Degraded Images Captured by a Camera on a Moving Object
title_fullStr Estimation and Sharpening of Blur in Degraded Images Captured by a Camera on a Moving Object
title_full_unstemmed Estimation and Sharpening of Blur in Degraded Images Captured by a Camera on a Moving Object
title_short Estimation and Sharpening of Blur in Degraded Images Captured by a Camera on a Moving Object
title_sort estimation and sharpening of blur in degraded images captured by a camera on a moving object
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877064/
https://www.ncbi.nlm.nih.gov/pubmed/35214538
http://dx.doi.org/10.3390/s22041635
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