High-energy industrial 2D X-ray imaging system with effective nonlocal means denoising for nondestructive testing
| Autor: | Heemoon Cho, Youngjin Lee, Seungwan Lee |
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| Rok vydání: | 2019 |
| Předmět: |
010302 applied physics
Physics Nuclear and High Energy Physics High energy business.industry Noise reduction Process (computing) 02 engineering and technology 021001 nanoscience & nanotechnology 01 natural sciences Imaging phantom Noise Contrast-to-noise ratio Computer Science::Computer Vision and Pattern Recognition Nondestructive testing 0103 physical sciences Image noise Computer vision Artificial intelligence 0210 nano-technology business Instrumentation |
| Zdroj: | Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 925:212-216 |
| ISSN: | 0168-9002 |
| Popis: | High-energy industrial X-ray imaging systems are widely used in the field of nondestructive testing for the detection of defects in mechanical material. To improve the defect detection ratio, it is highly important to reduce the amount of noise in this process. The purpose of this study is to develop a nonlocal means denoising algorithm in order to evaluate noise characteristics in a 450 kVp high-energy industrial X-ray imaging system. The analysis approach is tested on two phantom images, and image performance is evaluated by visual assessment, as well as the normalized noise power spectrum , contrast to noise ratio, and coefficient of variation. Improvement in image performance is attributed to the use of NLM denoising algorithm on high-energy industrial X-ray images, and results demonstrate that the proposed algorithm effectively reduces image noise. |
| Databáze: | OpenAIRE |
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