A robust approach for intensity loss compensation of TIRF microscopy images
TIRF microscopy is becoming increasingly popular in cell and molecular biology and opens a challenging computer vision application domain. However, time-lapse images, acquired by TIRF microscopy imaging system suffer the problem of intensity loss due to photobleaching. In this paper, TIRF images were segmented by a Gaussian mixture model into foreground and background. Parameters of the model were estimated through the expectation maximization. Finally, the restored image was wrapped backward to reference frame with the help of foreground parameters. The experimental results showed that the corrected images were effectively compensated and maintained a relatively constant intensity along time.
TIRF photobleaching compensation Gaussian mixture modeling expectation maximization
Xiangping Wu Linwei Chen Fangmin Yu
College of Information Engineering, China Jiliang University, Hangzhou 310018, PRC Acon Biotech (Hangzhou) Co., Ltd., Hangzhou 310023, PRC
国际会议
桂林
英文
1-5
2011-11-01（万方平台首次上网日期，不代表论文的发表时间）