Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
Image processing and data analysis: the multiscale approach
Image processing and data analysis: the multiscale approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Window Size Image De-noising Based on Intersection of Confidence Intervals (ICI) Rule
Journal of Mathematical Imaging and Vision
Morphological image sequence processing
Computing and Visualization in Science
Vector-Valued Image Regularization with PDEs: A Common Framework for Different Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Image Processing
Space-Time Adaptation for Patch-Based Image Sequence Restoration
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D wavelet subbands mixing for image denoising
Journal of Biomedical Imaging
Unsupervised patch-based image regularization and representation
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Fast non local means denoising for 3d MR images
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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We present a spatio-temporal filtering method for significantly increasing the signal-to-noise ratio (SNR) in noisy fluorescence microscopic image sequences where small particles have to be tracked from frame to frame. Image sequence restoration is achieved using a statistical approach involving an appropriate on-line window geometry specification. We have applied this method to noisy synthetic and real microscopic image sequences where a large number of small fluorescently labeled vesicles are moving in regions close to the Golgi apparatus. The SNR is shown to be drastically improved and the enhanced vesicles can be segmented. This novel approach can be further exploited for biological studies where the dynamics of small objects of interest have to be analyzed in molecular and sub-cellular bio-imaging.