Speckle reduction for medical ultrasound images with an expectation-maximization framework

In view of inherent speckle noise in medical images,a speckle reduction method was proposed based on an expectation-maximization(EM) framework.First,the real component of the in-phase/quadrature(I/Q) ultrasound image is extracted.Then,it is used to blindly estimate the point spread function(PSF) of the imaging system.Finally,based on the EM framework,an iterative algorithm alternating between the Wiener Filter and the anisotropic diffusion(AD) is exploited to produce despeckled images.The comparison experiment is carried out on both simulated and in vivo ultrasound images.It is shown that,with respect to the I/Q image,the proposed method averagely improves the speckle-signal-to-noise ratio(S-SNR) and the edge preservation index(β) of images by the factor of 1.94 and 7.52.Meanwhile,it averagely reduces the normalized mean-squared error(NMSE) by the factor of 3.95.The simulation and in vivo results indicates that the proposed method has a better overall performance than exited ones.     

Speckle noise reduction in digital holography by use of multiple polarization holograms

A novel speckle reduction technique for digital holography is proposed. Multiple off-axis holograms are recorded using a circularly polarized illumination beam and a rotating linearly polarized reference beam. The speckle noise in the reconstructed images is suppressed by averaging these fields. We demonstrate the effectiveness of this technique experimentally and conduct additional statistical evaluation.     

Speckle reduction algorithm for laser underwater image based on curvelet transform

Based on the analysis on the statistical model of speckle noise in laser underwater image, a novel speckle reduction algorithm using curvelet transform is proposed. Logarithmic transform is performed to transform the original multiplicative speckle noise into additive noise. An improved hard thresholding algorithm is applied in curvelet transform domain. The classical Monte-Carlo method is adopted to estimate the statistics of contourlet coefficients for speckle noise, thus determining the optimal threshold set. To further improve the visual quality of despeckling laser image, the cycle spinning technique is also utilized. Experimental results show that the proposed algorithm can achieve better performance than classical wavelet method and maintain more detail information.     

Speckle reduction algorithm for laser underwater image based on curvelet transform

Based on the analysis on the statistical model of speckle noise in laser underwater image, a novel speckle reduction algorithm using curvelet transform is proposed. Logarithmic transform is performed to transform the original multiplicative speckle noise into additive noise. An improved hard thresholding algorithm is applied in curvelet transform domain. The classical Monte-Carlo method is adopted to estimate the statistics of contourlet coefficients for speckle noise, thus determining the optimal threshold set. To further improve the visual quality of despeckling laser image, the cycle spinning technique is also utilized. Experimental results show that the proposed algorithm can achieve better performance than classical wavelet method and maintain more detail information.     

Speckle intensity images of target based on Monte Carlo method

Speckle intensity in the detector plane is deduced in the free-space optical system and imaging system based on Van Cittert-Zemike theorem. The speckle intensity images of plane target and conical target are obtained by using the Monte Carlo method and measured experimentally. The results show that when the range extent of target is smaller, the speckle size along the same direction become longer, and the speckle size increase with increasing incident light wavelengths. The speckle size increases and the speckle intensity images of target is closer to the actual object when the aperture scale augments. These findings are useful to access the target information by speckle in laser radar systems.     

High-quality three-dimensional holographic display with use of multiple fractional Fourier transform

In order to realize holographic display of three-dimensional （3D） objects and suppress zero-order light, conjugate image, and speckle noise, a novel method is proposed based on multiple fractional Fourier transform （M-FrFT） for cMculating holograms of 3D objects. A series of kinoforms are generated by adding pseudorandom phase factor （PPF） to object planes in calculating each kinoform, and generating the PPF randomly again in the next kinoform calculation. The reconstructed images from kinoform sequence are superposed together in order to suppress the speckle noise of reconstructed image and improve the contrast and detail resolution of the reconstructed images. The qualities of reconstructed images from single amplitude hologram, single kinoform, and kinoform sequence calculated by M-FrFT are compared. The effects of suppressing speckle noise are analyzed by calculating the speckle index of numerical reconstructed images. The analytical results illustrate that, with the proposed method for 3D holographic display, the zero-order light, conjugate image, and speckle noise can be suppressed, and the qualities of reconstructed images can be improved significantly.     

A miniature laser speckle fluorescence sectioning microscope for cell imaging

We present a miniature fluorescence sectioning microscope which uses a diode-pumped solid-state （DPSS） laser as the light source and a fast translating diffuser to produce dynamically changing speckle patterns onto the back aperture of the objective to illuminate the sample. Optical sectioning, which originates from the statistical characteristics of laser speckles, is obtained by calculating the contrast of a series of fluorescence images. High contrast fluorescence sectioning images of bovine pulmonary artery endothelial （BPAE） cells are obtained. The image quality is similar to that of the images acquired by standard laser scanning confocal microscope （LSCM）. Compared with LSCM, the laser speckle fluorescence microscope （LSFM） presented in this letter has many advantages, such as simple configurations, low cost, compact, and easy to operate, which makes it possible to have wide spread applications in biomedicine.     

Speckle Noise Suppressing Based on a Generalized Parallel Weighted-Average Multidirectional Morphological Filtering Algorithm

1 IntroductionThe coherent-imaging systems, such as LR(Laser Radar) and SAR(SyntheticAPerture Radar), generate images by coherent processing of the scattering echOsignals, so they are highly susceptible to speckle not,.Lll. The presence of speckle noise' in the images reduces the resolution and the tenet-explaining ability of the images.Thus it brings about an impact on the applications of the images and the detect~abilityof LR and SAR. However, removing speckle noise is one of the mos…     

An effective method for reducing speckle noise in digital holography

An effective method for reducing the speckle noise in digital holography is proposed in this paper.Different from the methods based on classical filtering technique,it utilizes the multiple holograms which are generated by rotating the illuminating light continuously.The intensity images reconstructed by a series of holograms generated by rotating the illuminating light possess different speckle patterns.Hence by properly averaging the reconstructed intensity fields,the speckle noises can be reduced greatly.Experimental results show that the proposed method is simple and effective to reduce speckle noise in digital holography.     

Recognizing the orbital angular momentum(OAM)of vortex beams from speckle patterns

The orbital angular momentum(OAM)of vortex beams offers a new degree for information encoding,which has been applied to optical communications.OAM measurement is essential for these applications,and has been realized in free space by several methods.However,these methods are inapplicable to estimate the OAM of vortex beams directly from the speckle patterns in the exit end of a multimode fiber(MMF).To tackle this issue,we design a convolutional neural network(CNN)to realize 100%accuracy recognition of two orthogonally polarized OAM modes from speckle patterns.Moreover,we demonstrate that even when the speckle patterns are cropped to only 1/64 of the original patterns,the recognition accuracy of the designed neural network is still higher than 98%.We also study the recognition accuracy of cropped speckles in different areas of speckle patterns to verify the feasibility of OAM recognition after cropping.The results demonstrate that recognizing the OAMs of two orthogonally polarized vortex beams from only a portion of speckle patterns in the exit end of an MMF is feasible,offering the potential to construct a 1×N data transmission scheme.