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...
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MDPI AG
2021-11-01
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| Online Access: | https://www.mdpi.com/1424-8220/21/21/7371 |
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| author | Jiyoung Lee Seunghyun Jang Jungbin Lee Taehan Kim Seonghan Kim Jongbum Seo Ki Hean Kim Sejung Yang |
| author_facet | Jiyoung Lee Seunghyun Jang Jungbin Lee Taehan Kim Seonghan Kim Jongbum Seo Ki Hean Kim Sejung Yang |
| author_sort | Jiyoung Lee |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T05:51:50Z |
| format | Article |
| id | doaj.art-427299bfb2774cb38893a22d023975fb |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:51:50Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-427299bfb2774cb38893a22d023975fb2023-11-22T21:40:37ZengMDPI AGSensors1424-82202021-11-012121737110.3390/s21217371Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic ImagesJiyoung Lee0Seunghyun Jang1Jungbin Lee2Taehan Kim3Seonghan Kim4Jongbum Seo5Ki Hean Kim6Sejung Yang7Department of Biomedical Engineering, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, KoreaDepartment of Biomedical Engineering, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, KoreaDepartment of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, KoreaDepartment of Biomedical Engineering, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, KoreaDepartment of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, KoreaDepartment of Biomedical Engineering, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, KoreaDepartment of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang 37673, KoreaDepartment of Biomedical Engineering, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju 26493, KoreaThe 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.https://www.mdpi.com/1424-8220/21/21/7371image fusionall-in-focusdepth of fieldmicroscopy |
| spellingShingle | Jiyoung Lee Seunghyun Jang Jungbin Lee Taehan Kim Seonghan Kim Jongbum Seo Ki Hean Kim Sejung Yang Multi-Focus Image Fusion Using Focal Area Extraction in a Large Quantity of Microscopic Images Sensors image fusion all-in-focus depth of field microscopy |
| 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 | image fusion all-in-focus depth of field microscopy |
| url | https://www.mdpi.com/1424-8220/21/21/7371 |
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