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Title: Non parametric denoising methods based on wavelets: Application to electron microscopy images in low exposure time

The 3D reconstruction of the Cryo-Transmission Electron Microscopy (Cryo-TEM) and Energy Filtering TEM images (EFTEM) hampered by the noisy nature of these images, so that their alignment becomes so difficult. This noise refers to the collision between the frozen hydrated biological samples and the electrons beam, where the specimen is exposed to the radiation with a high exposure time. This sensitivity to the electrons beam led specialists to obtain the specimen projection images at very low exposure time, which resulting the emergence of a new problem, an extremely low signal-to-noise ratio (SNR). This paper investigates the problem of TEM images denoising when they are acquired at very low exposure time. So, our main objective is to enhance the quality of TEM images to improve the alignment process which will in turn improve the three dimensional tomography reconstructions. We have done multiple tests on special TEM images acquired at different exposure time 0.5s, 0.2s, 0.1s and 1s (i.e. with different values of SNR)) and equipped by Golding beads for helping us in the assessment step. We herein, propose a structure to combine multiple noisy copies of the TEM images. The structure is based on four different denoising methods, to combine themore » multiple noisy TEM images copies. Namely, the four different methods are Soft, the Hard as Wavelet-Thresholding methods, Bilateral Filter as a non-linear technique able to maintain the edges neatly, and the Bayesian approach in the wavelet domain, in which context modeling is used to estimate the parameter for each coefficient. To ensure getting a high signal-to-noise ratio, we have guaranteed that we are using the appropriate wavelet family at the appropriate level. So we have chosen âĂIJsym8âĂİ wavelet at level 3 as the most appropriate parameter. Whereas, for the bilateral filtering many tests are done in order to determine the proper filter parameters represented by the size of the filter, the range parameter and the spatial parameter respectively. The experiments reported in this paper demonstrate the performance of the Bilateral Filtering and the Bayesian approaches in terms of improving the SNRout and the image quality. Taken together, these results suggest that the Bayesian process has a potential to outperform all the used methods, where in the multiple noisy copies structure it gave us the best SNRout without change of the golden beads diameter. The Bayesian approach yielded enhanced average image without needing a huge amount of copies.« less
Authors:
 [1] ;  [2] ;  [3] ; ; ;  [4]
  1. Science and Technology Faculty, El Bachir El Ibrahimi University, BordjBouArreridj (Algeria)
  2. Laboratory of Electrical Engineering(LGE), University of M'sila (Algeria)
  3. Polytechnic School, University of Tours (EPU - PolytechTours), EPU - Energy and Electronics Department (France)
  4. INSERMU759, University Campus Orsay, 91405 Orsay Cedex (France)
Publication Date:
OSTI Identifier:
22390869
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1641; Journal Issue: 1; Conference: MAXENT 2014: Conference on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Clos Luce, Amboise (France), 21-26 Sep 2014; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALIGNMENT; COMPUTERIZED SIMULATION; ELECTRON BEAMS; FILTERS; GOLD; IMAGES; NOISE; NONLINEAR PROBLEMS; POTENTIALS; SENSITIVITY; SIGNAL-TO-NOISE RATIO; THREE-DIMENSIONAL CALCULATIONS; TOMOGRAPHY; TRANSMISSION ELECTRON MICROSCOPY