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23 October 1996 Wavelet-based denoising methods: a comparative study with applications in microscopy
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This paper describes different methodologies for noise reduction or denoising with applications in the field of microscopy. An in depth study on wavelet- and polynomial based denoising has been performed by considering standard test images and phantom tests with moderate and high levels of Gaussian noise. Different thresholding methods have been tested and evaluated and in particular a novel sigmoidal- type thresholding method has been proposed. In real applications, noise variance estimation problem becomes crucial because most of the thresholding estimators tends to overestimate this value. A comparison with the Hermite polynomial transform (HPT) and a modification of the HPT based in detecting the position and orientation of relevant edges has been accomplished. From this study one can conclude that both wavelet-based and polynomial-based denoising methods perform better than any other nonlinear filtering method both in terms of perceptual quality and edge-preserving characteristics.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gabriel Cristobal, Monica Chagoyen, Boris Escalante-Ramirez, and Juan R. Lopez "Wavelet-based denoising methods: a comparative study with applications in microscopy", Proc. SPIE 2825, Wavelet Applications in Signal and Image Processing IV, (23 October 1996);

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