Title :
Denoising for bio-image sequences via matrix decomposition
Author :
Qian Li ; Lei Qi ; Guoqiang Bi ; Weiping Li
Author_Institution :
Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
Calcium fluorescence imaging is a useful tool in life sciences for visualization of calcium signal in neuronal networks. During the imaging process, noise is inevitably introduced into the image sequences and affects their usefulness. Therefore, noise reduction is an important image processing task for such bio-images. In this paper, a scheme based on matrix decomposition is proposed to denoise this class of bio-image sequences by exploiting the data characteristics. Experimental results have validated the denoising scheme for the class of bio-image sequences.
Keywords :
fluorescence; image denoising; image sequences; matrix decomposition; neural nets; bio-image sequences; calcium fluorescence imaging; calcium signal; denoising; imaging process; life sciences; matrix decomposition; neuronal networks; noise reduction; visualization; Calcium; Imaging; Matrix decomposition; Neurons; Noise; Noise reduction; Transient analysis; bio-image denoising; low-rank; matrix decomposition; sparse; total variation;
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2014 IEEE China Summit & International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4799-5401-8
DOI :
10.1109/ChinaSIP.2014.6889296
