We present a new method, referred to as phase correlation imaging (PCI), to study cell dynamics and function through temporal phase correlation analysis. PCI offers label-free, high-performance, simple-design, as well as suitability for operation in a conventional microscopy setting. PCI works without the need for controlled or synchronized photoactivation and sophisticated acquisition schemes, and only involves taking a sequence of phase images. The PCI image incorporates information on the phase fluctuations induced by both Brownian motion and deterministic motion of intracellular transport across large scales. We employed spatial light interference microscopy (SLIM) recently developed in our laboratory to experimentally measure quantitative phase information which renders the thickness and refractive index of cellular components without adding contrast agents. The acquisition process is repeated to obtain time-lapse phase images. We calculate the correlation time at each pixel for acquired time-lapse phase images and obtain the correlation time map in space. By temporal correlation analysis, PCI reveals cell dynamics information, which is complementary to quantitative phase imaging itself.
Holography, in which three-dimensional (3D) information and texture of object is encoded with interference fringe is a
promising approach for 3D display. However, it is challenge to make photographic hologram of living object. In addition,
it is impossible to record scene combining real-existing objects with virtual ones using photographic holography. In this
paper, we propose a method for capturing and displaying 3D real-existing scene. Firstly, the 3D shape and color texture
of scene is captured with fringe projection method. Secondly, the information of scene is encoded with computer
generated fringe, which is called Computer-generated Hologram (CGH). Finally, the CGH is materialize as hardcopy or
transferred to spatial light modulator (SLM) for display. The real-color Rainbow-hologram is chosen for display static
scene. Three Fresnel holograms corresponding to red, green and blue component of scene are adopted for display
dynamic scene. The apparatuses for 3D capture and display are introduced and the experimental results are
The tomographic refractive index imaging technique by digital holographic microscopy with sample rotation is presented. First, transmission phase images are numerically reconstructed from holograms acquired at regularly-spaced angular positions for the rotating sample. Then, the three-dimensional refractive index spatial distribution is reconstructed by filtered back-projection algorithm. Last, the experiments are carried out and the three-dimensional refractive index distribution of single-mode and single-mode polarization maintaining optical fibers is accurately reconstructed.
A fundamental problem in optical and digital holography is the existence of speckle noise in the reconstructed image.
Many approaches have been carried out in order to overcome this problem. In this paper a new technique to reduce the
speckle noise is proposed based on the physical nature of speckle noise. The illumination direction of the object beam is
changed to provide a different phase information for the same recorded object in an off-axis digital holographic setup
and the holograms are recorded with different illumination directions. Then the intensity information of the reconstructed
images is superposed and averaged to reduce the speckle noise. The theoretical analysis and experimental results are
shown to valid our proposal. They prove that the technique can effectively reduce the speckle noise without ruining the
In this paper, we introduce the potentialities of the digital hologram for the three-dimensional shape measurement from
numerical reconstructed image. The image processing of the Fresnel digital hologram recorded by CCD sensor and the
algorithm for 3d shape reconstruction is taken into account. Firstly, we stitch a series of small digital holograms to obtain a
hologram with larger size. Secondly, the reconstructed image sequences of different depth planes are obtained by
numerical reconstructing hologram. Finally, the depth information of each sample point of object is gained by algorithm of
focus measure evaluation, in which the maximum focus measure of a region is found by the grey level variance of image
sequence. The basic principle of this technique and its experimental verification are presented.
Dynamics of (1+1)D spatial solitons in photorefractive medium with drift and diffusion nonlinearity
is investigated. Propagation of solitons is analyzed theoretically by means of effective-particle approach
method. The explicit formula of acceleration of soltion is derived. Analytical results show that the solitons
evolve with a constant acceleration along a parabolic trajectory. The acceleration is determined by the
input soliton and the diffusion nonlinearity. We also simulate the propagation of solitons numerically and
excellent agreements are obtained between the theoretical and numerical results.
In this paper, we present a new segmentation method in which Curvelet transform(CT) acts as an edge enhancement tool to modify diffusion marching. Firstly image segmentation is modeled via CT boundary emphasizing and lorentzian-function based diffusion. By means of multi-scale decomposition and multi-directional projection, CT detects pixels which are not obvious at pixel-level, but detectable by integrating over many pixels. Furthermore, projections inside Curvelet calculation directly lead to noise averaging, thus CT could be employed to retain weak edges and remove noises simultaneously when diffusion evolve to a certain extent. Secondly, a criterion is proposed to seek the appropriate moment for CT adoption during diffusion. It is fulfilled by analyzing histogram maxima every thirty iterations. If the count reduced between 2 maxima calculations arrives a threshold, CT will be performed to prevent edge disappearing. Thirdly, segmentation quality is measured to determine the cessation of diffusion. We carry out segmentation at the time when CT is completed or every fifty iterations finished. The partitioning numbers between two adjacent segmentations are compared to judge whether diffusion should be ceased. Experiments show that our approach takes CT's advantages of edge-preserving and denoising, it yields an efficient segmentation than the classical PDE does.
This paper presents s new scheme for face localization in a complex background. A Difference Offset of Gaussian filter is first introduced to calculate a feature inertia surface of an image. Then skeletonization on the inertia surface is carried out by a combination of fast construction of Euclidean Distance Maps and morphological operations. After that, face regions in this resulting skeleton image are detected by a quadratic Gabor filter, and its face trueness of each located area is verified by a modified retinal model. Experiments in practical applications have shown its feasibility.