Cargando…

Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images

The non-invasive examination of conjunctival goblet cells using a microscope is a novel procedure for the diagnosis of ocular surface diseases. However, it is difficult to generate an all-in-focus image due to the curvature of the eyes and the limited focal depth of the microscope. The microscope ac...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Jiyoung, Jang, Seunghyun, Lee, Jungbin, Kim, Taehan, Kim, Seonghan, Seo, Jongbum, Kim, Ki Hean, Yang, Sejung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8586970/
https://www.ncbi.nlm.nih.gov/pubmed/34770677
http://dx.doi.org/10.3390/s21217371
_version_ 1784597991640793088
author Lee, Jiyoung
Jang, Seunghyun
Lee, Jungbin
Kim, Taehan
Kim, Seonghan
Seo, Jongbum
Kim, Ki Hean
Yang, Sejung
author_facet Lee, Jiyoung
Jang, Seunghyun
Lee, Jungbin
Kim, Taehan
Kim, Seonghan
Seo, Jongbum
Kim, Ki Hean
Yang, Sejung
author_sort Lee, Jiyoung
collection PubMed
description The non-invasive examination of conjunctival goblet cells using a microscope is a novel procedure for the diagnosis of ocular surface diseases. However, it is difficult to generate an all-in-focus image due to the curvature of the eyes and the limited focal depth of the microscope. The microscope acquires multiple images with the axial translation of focus, and the image stack must be processed. Thus, we propose a multi-focus image fusion method to generate an all-in-focus image from multiple microscopic images. First, a bandpass filter is applied to the source images and the focus areas are extracted using Laplacian transformation and thresholding with a morphological operation. Next, a self-adjusting guided filter is applied for the natural connections between local focus images. A window-size-updating method is adopted in the guided filter to reduce the number of parameters. This paper presents a novel algorithm that can operate for a large quantity of images (10 or more) and obtain an all-in-focus image. To quantitatively evaluate the proposed method, two different types of evaluation metrics are used: “full-reference” and “no-reference”. The experimental results demonstrate that this algorithm is robust to noise and capable of preserving local focus information through focal area extraction. Additionally, the proposed method outperforms state-of-the-art approaches in terms of both visual effects and image quality assessments.
format Online
Article
Text
id pubmed-8586970
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-85869702021-11-13 Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images Lee, Jiyoung Jang, Seunghyun Lee, Jungbin Kim, Taehan Kim, Seonghan Seo, Jongbum Kim, Ki Hean Yang, Sejung Sensors (Basel) Communication The non-invasive examination of conjunctival goblet cells using a microscope is a novel procedure for the diagnosis of ocular surface diseases. However, it is difficult to generate an all-in-focus image due to the curvature of the eyes and the limited focal depth of the microscope. The microscope acquires multiple images with the axial translation of focus, and the image stack must be processed. Thus, we propose a multi-focus image fusion method to generate an all-in-focus image from multiple microscopic images. First, a bandpass filter is applied to the source images and the focus areas are extracted using Laplacian transformation and thresholding with a morphological operation. Next, a self-adjusting guided filter is applied for the natural connections between local focus images. A window-size-updating method is adopted in the guided filter to reduce the number of parameters. This paper presents a novel algorithm that can operate for a large quantity of images (10 or more) and obtain an all-in-focus image. To quantitatively evaluate the proposed method, two different types of evaluation metrics are used: “full-reference” and “no-reference”. The experimental results demonstrate that this algorithm is robust to noise and capable of preserving local focus information through focal area extraction. Additionally, the proposed method outperforms state-of-the-art approaches in terms of both visual effects and image quality assessments. MDPI 2021-11-05 /pmc/articles/PMC8586970/ /pubmed/34770677 http://dx.doi.org/10.3390/s21217371 Text en © 2021 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 Communication
Lee, Jiyoung
Jang, Seunghyun
Lee, Jungbin
Kim, Taehan
Kim, Seonghan
Seo, Jongbum
Kim, Ki Hean
Yang, Sejung
Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images
title Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images
title_full Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images
title_fullStr Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images
title_full_unstemmed Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images
title_short Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images
title_sort multi-focus image fusion using focal area extraction in a large quantity of microscopic images
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8586970/
https://www.ncbi.nlm.nih.gov/pubmed/34770677
http://dx.doi.org/10.3390/s21217371
work_keys_str_mv AT leejiyoung multifocusimagefusionusingfocalareaextractioninalargequantityofmicroscopicimages
AT jangseunghyun multifocusimagefusionusingfocalareaextractioninalargequantityofmicroscopicimages
AT leejungbin multifocusimagefusionusingfocalareaextractioninalargequantityofmicroscopicimages
AT kimtaehan multifocusimagefusionusingfocalareaextractioninalargequantityofmicroscopicimages
AT kimseonghan multifocusimagefusionusingfocalareaextractioninalargequantityofmicroscopicimages
AT seojongbum multifocusimagefusionusingfocalareaextractioninalargequantityofmicroscopicimages
AT kimkihean multifocusimagefusionusingfocalareaextractioninalargequantityofmicroscopicimages
AT yangsejung multifocusimagefusionusingfocalareaextractioninalargequantityofmicroscopicimages