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Wavelet‐based image restoration for compact X‐ray microscopy
Author(s) -
Stollberg H.,
Boutet De Monvel J.,
Holmberg A.,
Hertz H. M.
Publication year - 2003
Publication title -
journal of microscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.569
H-Index - 111
eISSN - 1365-2818
pISSN - 0022-2720
DOI - 10.1046/j.1365-2818.2003.01211.x
Subject(s) - thresholding , discrete wavelet transform , wavelet , artificial intelligence , noise reduction , noise (video) , microscopy , wavelet transform , pattern recognition (psychology) , signal to noise ratio (imaging) , computer vision , image quality , computer science , signal (programming language) , optics , mathematics , materials science , image (mathematics) , physics , programming language
Summary Compact water‐window X‐ray microscopy with short exposure times will always be limited on photons owing to sources of limited power in combination with low‐efficency X‐ray optics. Thus, it is important to investigate methods for improving the signal‐to‐noise ratio in the images. We show that a wavelet‐based denoising procedure significantly improves the quality and contrast in compact X‐ray microscopy images. A non‐decimated, discrete wavelet transform (DWT) is applied to original, noisy images. After applying a thresholding procedure to the finest scales of the DWT, by setting to zero all wavelet coefficients of magnitude below a prescribed value, the inverse DWT to the thresholded DWT produces denoised images. It is concluded that the denoising procedure has potential to reduce the exposure time by a factor of 2 without loss of relevant image information.