Digital speckle reduction in holograms – a comparison between methods Adrian Stern a1 , Vladimir Farber a , Amitai Uzan a , Yair Rivenson b a Department of Electro-Optical Engineering, Ben-Gurion University of the Negev; b Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev ABSTRACT Digital holography, as any other coherent imaging modalities, is subject to speckle noise. Speckles may degrade significantly the image quality, therefore many optical and digital techniques were developed to suppress the speckles. In this paper we present a comparison between six digital speckle filtering techniques used for digital holography. Keywords: Digital Holography, Speckle denoising 1. INTRODUCTION Coherent imaging modalities such as digital holography are subject to speckle noise that may impose severe limitations on the image quality. Speckle noise causes to a signal depended distortion of the image which makes it difficult to identify small details in the image. Speckle occurs whenever coherent light passes through a randomly fluctuating medium, or is reflected from a rough surface, where the latter case is of particular interest in digital holography. Speckle noise manifests as temporal or spatial fluctuations, depending on the speckle source. Speckle pattern dependence in time refers to as dynamic speckle pattern. If the speckle grains formation, destruction and movement are random, then, this speckle form is called "boiling pattern". Spatial speckles, commonly formatted by surface roughness, are the more common in digital holography. Description of the speckle noise mechanism and their appropriate models can be found in Refs. 1, 2 . Unlike thermal and readout noise, speckle noise is object dependent, with a variance being proportional to the local field intensity. The lateral speckle average size can be approximated as the reciprocal of the maximum spatial frequency, to have a value of D z  , where λ is the wavelength, D is the critical aperture (typically the hologram lateral size) and z is the propagation distance 1, 2 . The intensity distribution of the speckle noise obeys a negative exponential statistics, having a standard deviation equal to the mean value. The complex field amplitude contaminated by speckle noise follows a Rician distribution 1 . Numerous techniques were developed to reduce the speckles in digital holography. The speckle suppression techniques can be categorized grossly into two main groups: acquisition improving process (optical techniques) and post processing filtering methods (image processing techniques). Techniques in the first category attempt to invert translational speckle (for fixed object) into "boiling speckle " and by this to generate local statistics that can be used to remove the noise, for instance by time averaging. The second category consists of post processing digital filtering techniques that attempt to extract the object information contained within a single hologram acquisition by utilizing assumptions about the object (e.g. smoothness, sparsity) and the appropriate noise model. In this paper we compare some classical and state-off-the art techniques from the second category. When there is no flexibility in the acquisition design the only way to cope with the speckles is to digitally filter them after acquisition. Several digital filtering techniques for the reduction of speckle noise in DH have been developed 3-9 . Numerous digital filtering methods have also been developed for other coherent imaging modalities that encounter speckle noise (e.g. ultrasound, radar, microwave). Among the best known are the Lee filter 10 , Kuan filter 11 , Frost filter 12 , Bi-lateral filter 13-15 and Wavelet threshold filter 16 . Some hybrid filters were developed, such as Wavelet domain Total Variation (TV) filter 17 , Bi-lateral Wavelet filtering 15 . Asymptotically, all coherent imaging modalities (acoustic, radar, microwave, DH in the visible) share the same speckle noise model. Therefore filtering methods developed for other 1 stern@bgu.ac.il Three-Dimensional Imaging, Visualization, and Display 2014, edited by Bahram Javidi, Jung-Young Son, Osamu Matoba, Manuel Martínez-Corral, Adrian Stern, Proc. of SPIE Vol. 9117, 91170C © 2014 SPIE · CCC code: 0277-786X/14/$18 · doi: 10.1117/12.2049829 Proc. of SPIE Vol. 9117 91170C-1 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 11/17/2014 Terms of Use: http://spiedl.org/terms