ArticleSensors (Basel, Switzerland)2020
Effectiveness of Non-Local Means Algorithm with an Industrial 3 MeV LINAC High-Energy X-Ray System for Non-Destructive Testing.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- An image processing technique for optimizing industrial defect detection using dehazing algorithms.PloS one · 2025Article
- Exploring the Impact of Noise and Image Quality on Deep Learning Performance in DXA Images.Diagnostics (Basel, Switzerland) · 2024Article
- Investigation of Deconvolution Method with Adaptive Point Spread Function Based on Scintillator Thickness in Wavelet Domain.Bioengineering (Basel, Switzerland) · 2024Article
- Renal Pathology Images Segmentation Based on Improved Cuckoo Search with Diffusion Mechanism and Adaptive Beta-Hill Climbing.Journal of bionic engineering · 2023Article
- Characterization of Flexible Amorphous Silicon Thin-Film Transistor-Based Detectors with Positive-Intrinsic-Negative Diode in Radiography.Diagnostics (Basel, Switzerland) · 2022Article
- Quantitative and Comparative Analysis of Effectivity and Robustness for Enhanced and Optimized Non-Local Mean Filter Combining Pixel and Patch Information on MR Images of Musculoskeletal System.Sensors (Basel, Switzerland) · 2021Article
- KL-MOB: automated COVID-19 recognition using a novel approach based on image enhancement and a modified MobileNet CNN.PeerJ. Computer science · 2021Article
- Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising.Materials (Basel, Switzerland) · 2020Article
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Authors and funding
3 authors.
Funding
Abstract
Industrial high-energy X-ray imaging systems are widely used for non-destructive testing (NDT) to detect defects in the internal structure of objects. Research on X-ray image noise reduction techniques using image processing has been widely conducted with the aim of improving the detection of defects in objects. In this paper, we propose a non-local means (NLM) denoising algorithm to improve the quality of images obtained using an industrial 3 MeV high-energy X-ray imaging system. We acquired X-ray images using various castings and assessed the performance visually and by obtaining the intensity profile, contrast-to-noise ratio, coefficient of variation, and normalized noise power spectrum. Overall, the quality of images processed by the proposed NLM algorithm is superior to those processed by existing algorithms for the acquired casting images. In conclusion, the NLM denoising algorithm offers an efficient and competitive approach to overcome the noise problem in high-energy X-ray imaging systems, and we expect the accompanying image processing software to facilitate and improve image restoration.
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