Frames-Based Denoising in 3D Confocal Microscopy Imaging.
In this paper, we propose a novel denoising method for 3D confocal microscopy data based on robust edge detection. Our approach relies on the construction of a non-separable frame system in 3D that incorporates the Sobel operator in dual spatial directions. This multidirectional set of digital filters is capable of robustly detecting edge information by ensemble thresholding of the filtered data. We demonstrate the application of our method to both synthetic and real confocal microscopy data by comparing it to denoising methods based on separable 3D wavelets and 3D median filtering, and report very encouraging results.
Konstantinidis
Ioannis
I
Computational Biomedicine Lab (formerly known as Visual Computing Lab), Department of Computer Science, University of Houston, Texas 77204, USA.
Santamaria-Pang
Alberto
A
Kakadiaris
Ioannis
I