title: Blind source separation based x-ray image denoising from an image sequence.
abstract: Blind source separation (BSS) based x-ray image denoising from an image sequence is proposed. Without priori knowledge, the useful image signal can be separated from an x-ray image sequence, for original images are supposed as different combinations of stable image signal and random image noise. The BSS algorithms such as fixed-point independent component analysis and second-order statistics singular value decomposition are used and compared with multi-frame averaging which is a common algorithm for improving image's signal-to-noise ratio (SNR). Denoising performance is evaluated in SNR, standard deviation, entropy, and runtime. Analysis indicates that BSS is applicable to image denoising; the denoised image's quality will get better when more frames are included in an x-ray image sequence, but it will cost more time; there should be trade-off between denoising performance and runtime, which means that the number of frames included in an image sequence is enough.
authors.affiliation: School of Optoelectronic Engineering, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing 210023, China.
authors.forename: Chun-Yu
authors.initials: CY
authors.lastname: Yu
authors.affiliation: School of Optoelectronic Engineering, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing 210023, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Li
authors.affiliation: School of Optoelectronic Engineering, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing 210023, China.
authors.forename: Bin
authors.initials: B
authors.lastname: Fei
authors.affiliation: School of Optoelectronic Engineering, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing 210023, China.
authors.forename: Wei-Liang
authors.initials: WL
authors.lastname: Li