An intelligent system for lung CT image denoising using a hybrid WT-NLM filter
Image denoising is an extensively researched problem in computer vision that is commonly used as a benchmark for many imaging tasks. Noise distorts an image throughout the acquisition and transmission cycle. The elimination of noise from the original image is a significant challenge for scientists a...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-04-01
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| Series: | Automatika |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/00051144.2025.2460885 |
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| author | S.L. Soniya T. Ajith Bosco Raj |
| author_facet | S.L. Soniya T. Ajith Bosco Raj |
| author_sort | S.L. Soniya |
| collection | DOAJ |
| description | Image denoising is an extensively researched problem in computer vision that is commonly used as a benchmark for many imaging tasks. Noise distorts an image throughout the acquisition and transmission cycle. The elimination of noise from the original image is a significant challenge for scientists and this work considers Gaussian, Salt and pepper noises, as medical images are prone to it. Hence, this work presents ways for mitigating noise, while preserving the relevant image information. In this study, a Hybrid Wavelet Transform with Non-Local Mean (Hybrid WT-NLM) filter is proposed for reducing noise in lung CT images. The final denoised images are formed by the summation of NLM-filtered images and wavelet coefficients. The proposed study offers a straightforward method for removing noise to attain better visual quality in a reasonable period. The efficacy of the proposed denoising approach is proven by comparing it with traditional denoising approaches such as Morphological filtering, Mean Filter, Median filter, Adaptive median filter and Non-Local Means (NLM) upon two public datasets such as Public LIDC database and in-house clinical ICCN database. The average PSNR of the proposed work is 25.47 dB at a time consumption of 1.03 s. |
| format | Article |
| id | doaj-art-84e4646b581e484e9d8edeeb5ac28ad5 |
| institution | Kabale University |
| issn | 0005-1144 1848-3380 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Automatika |
| spelling | doaj-art-84e4646b581e484e9d8edeeb5ac28ad52025-02-06T14:35:08ZengTaylor & Francis GroupAutomatika0005-11441848-33802025-04-0166218820010.1080/00051144.2025.2460885An intelligent system for lung CT image denoising using a hybrid WT-NLM filterS.L. Soniya0T. Ajith Bosco Raj1Department of Computer Science and Engineering, St. Xavier’s Catholic College of Engineering, Nagercoil, IndiaDepartment of Electronics and Communication Engineering, PSN College of Engineering and Technology, Tirunelveli, IndiaImage denoising is an extensively researched problem in computer vision that is commonly used as a benchmark for many imaging tasks. Noise distorts an image throughout the acquisition and transmission cycle. The elimination of noise from the original image is a significant challenge for scientists and this work considers Gaussian, Salt and pepper noises, as medical images are prone to it. Hence, this work presents ways for mitigating noise, while preserving the relevant image information. In this study, a Hybrid Wavelet Transform with Non-Local Mean (Hybrid WT-NLM) filter is proposed for reducing noise in lung CT images. The final denoised images are formed by the summation of NLM-filtered images and wavelet coefficients. The proposed study offers a straightforward method for removing noise to attain better visual quality in a reasonable period. The efficacy of the proposed denoising approach is proven by comparing it with traditional denoising approaches such as Morphological filtering, Mean Filter, Median filter, Adaptive median filter and Non-Local Means (NLM) upon two public datasets such as Public LIDC database and in-house clinical ICCN database. The average PSNR of the proposed work is 25.47 dB at a time consumption of 1.03 s.https://www.tandfonline.com/doi/10.1080/00051144.2025.2460885Image denoisinglung CT imageimage qualityNLM filterfilter-based approach |
| spellingShingle | S.L. Soniya T. Ajith Bosco Raj An intelligent system for lung CT image denoising using a hybrid WT-NLM filter Automatika Image denoising lung CT image image quality NLM filter filter-based approach |
| title | An intelligent system for lung CT image denoising using a hybrid WT-NLM filter |
| title_full | An intelligent system for lung CT image denoising using a hybrid WT-NLM filter |
| title_fullStr | An intelligent system for lung CT image denoising using a hybrid WT-NLM filter |
| title_full_unstemmed | An intelligent system for lung CT image denoising using a hybrid WT-NLM filter |
| title_short | An intelligent system for lung CT image denoising using a hybrid WT-NLM filter |
| title_sort | intelligent system for lung ct image denoising using a hybrid wt nlm filter |
| topic | Image denoising lung CT image image quality NLM filter filter-based approach |
| url | https://www.tandfonline.com/doi/10.1080/00051144.2025.2460885 |
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