ArticleSensors (Basel, Switzerland)2022
Improved Adaptive Kalman-Median Filter for Line-Scan X-ray Transmission Image.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Domain-specific simulated data enhances knife-mark noise suppression in microscopy images of materials.Microscopy (Oxford, England) · 2026Article
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2 authors.
Funding
Abstract
With their wide application in industrial fields, the denoising and/or filtering of line-scan images is becoming more important, which also affects the quality of their subsequent recognition or classification. Based on the application of single source dual-energy X-ray transmission (DE-XRT) line-scan in-line material sorting and the different horizontal and vertical characteristics of line-scan images, an improved adaptive Kalman-median filter (IAKMF) was proposed for several kinds of noises of an energy integral detector. The filter was realized through the determination of the off-line noise total covariance, the covariance distribution coefficient between the process noise and measurement noise, the adaptive covariance scale coefficient, calculation scanning mode and single line median filter. The experimental results show that the proposed filter has the advantages of simple code, good real-time control, high precision, small artifacts, convenience and practicality. It can take into account the filtering of high-frequency random noise, the retention of low-frequency real signal fluctuation and the preservation of shape features. The filter also has a good practical application value and can be improved and extended to other line-scan image filtering scenarios.
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