The discriminative bilateral filter: an enhanced denoising filter for electron microscopy data.
Advances in three-dimensional (3D) electron microscopy (EM) and image processing are providing considerable improvements in the resolution of subcellular volumes, macromolecular assemblies and individual proteins. However, the recovery of high-frequency information from biological samples is hindered by specimen sensitivity to beam damage. Low dose electron cryo-microscopy conditions afford reduced beam damage but typically yield images with reduced contrast and low signal-to-noise ratios (SNRs). Here, we describe the properties of a new discriminative bilateral (DBL) filter that is based upon the bilateral filter implementation of Jiang et al. (Jiang, W., Baker, M.L., Wu, Q., Bajaj, C., Chiu, W., 2003. Applications of a bilateral denoising filter in biological electron microscopy. J. Struc. Biol. 128, 82-97.). In contrast to the latter, the DBL filter can distinguish between object edges and high-frequency noise pixels through the use of an additional photometric exclusion function. As a result, high frequency noise pixels are smoothed, yet object edge detail is preserved. In the present study, we show that the DBL filter effectively reduces noise in low SNR single particle data as well as cellular tomograms of stained plastic sections. The properties of the DBL filter are discussed in terms of its usefulness for single particle analysis and for pre-processing cellular tomograms ahead of image segmentation.
Pantelic
Radosav S
RS
Institute for Molecular Bioscience, University of Queensland, Brisbane, Qld 4072, Australia.
Rothnagel
Rosalba
R
Huang
Chang-Yi
CY
Muller
David
D
Woolford
David
D
Landsberg
Michael J
MJ
McDowall
Alasdair
A
Pailthorpe
Bernard
B
Young
Paul R
PR
Banks
Jasmine
J
Hankamer
Ben
B
Ericksson
Geoffery
G
D000818:Animals; D016477:Artifacts; D016367:Baculoviridae; D002478:Cells, Cultured; D020285:Cryoelectron Microscopy; D005293:Ferritins / Q000032:analysis; D006433:Hemocyanins / Q000032:analysis; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional; D019476:Insect Proteins / Q000032:analysis; D050417:Insulin-Secreting Cells / Q000737:chemistry; D008854:Microscopy, Electron / Q000379:methods*; D010363:Pattern Recognition, Automated; D014057:Tomography, X-Ray Computed
D019476:Insect Proteins; D005293:Ferritins; D006433:Hemocyanins; C032808:keyhole-limpet hemocyanin