条纹
噪音(视频)
降噪
衰减
投影(关系代数)
工件(错误)
计算机科学
探测器
散粒噪声
人工智能
算法
计算机视觉
物理
光学
图像(数学)
作者
Ymir Mäkinen,Stefano Marchesini,Alessandro Foi
标识
DOI:10.1107/s1600577522002739
摘要
X-ray micro-tomography systems often suffer from high levels of noise. In particular, severe ring artifacts are common in reconstructed images, caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. Furthermore, the projections commonly contain high levels of Poissonian noise arising from the photon-counting detector. This work presents a 3-D multiscale framework for streak attenuation through a purposely designed collaborative filtering of correlated noise in volumetric data. A distinct multiscale denoising step for attenuation of the Poissonian noise is further proposed. By utilizing the volumetric structure of the projection data, the proposed fully automatic procedure offers improved feature preservation compared with 2-D denoising and avoids artifacts which arise from individual filtering of sinograms.
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