Albertina Castro

Resistance of the double random phase encryption against various attacks

Several attacks are proposed against the double random phase encryption scheme. These attacks are demonstrated on computer-generated ciphered images. The scheme is shown to be resistant against brute force attacks but susceptible to chosen and known plaintext attacks. In particular, we describe a technique to recover the exact keys with only two known plain images. We compare this technique to other attacks proposed in the literature.

Reduction of speckle in digital holography by discrete Fourier filtering

We present a digital signal processing technique that reduces the speckle content in reconstructed digital holograms. The method is based on sequential sampling of the discrete Fourier transform of the reconstructed image field. Speckle reduction is achieved at the expense of a reduced intensity and resolution, but this trade-off is shown to be greatly superior to that imposed by the traditional mean and median filtering techniques. In particular, we show that the speckle can be reduced by half with no loss of resolution (according to standard definitions of both metrics).

Integral imaging with large depth of field using an asymmetric phase mask

We propose to improve the depth of field of Integral Imaging systems by combining an array of phase masks with the traditional lenslet array. We show that obtained elemental images are sharp over a larger range than with a regular lenslet array. We further increase the quality of elemental images by a digital restauration. Computer simulations of pickup and reconstruction are presented.

Comparison of passive ranging integral imaging and active imaging digital holography for three-dimensional object recognition

We present an overview of three-dimensional (3D) object recognition techniques that use active sensing by interferometric imaging (digital holography) and passive sensing by integral imaging. We describe how each technique can be used to retrieve the depth information of a 3D scene and how this information can then be used for 3D object recognition. We explore various algorithms for 3D recognition such as nonlinear correlation and target distortion tolerance. We also provide a comparison of the advantages and disadvantages of the two techniques.

Depth-independent segmentation of macroscopic three-dimensional objects encoded in single perspectives of digital holograms

We present a technique for performing segmentation of macroscopic three-dimensional objects recorded using in-line digital holography. We numerically reconstruct a single perspective of each object at a range of depths. At each point in the digital wavefront we calculate variance about a neighborhood. The maximum variance at each point over all depths is thresholded to classify it as an object pixel or a background pixel. Segmentation results for objects of low and high contrast are presented.

Security analysis of optical encryption

This paper analyzes the security of amplitude encoding for double random phase encryption. We describe several types of attack. The system is found to be resistant to brute-force attacks but vulnerable to chosen and known plaintext attacks.

Bow-tie effect: differential operator.

We propose to use a differential operator for representing the influence of phase-only filters on the defocused modulation transfer function of the clear pupil aperture. We present a phase-only filter that implements optically Taylors theorem in phase space. We show numerical simulations of the modulation transfer functions and the images that can be obtained by using the proposed filter.

Pose estimation from a two-dimensional view by use of composite correlation filters and neural networks

We present a technique to estimate the pose of a three-dimensional object from a two-dimensional view. We first compute the correlation between the unknown image and several synthetic-discriminant-function filters constructed with known views of the object. We consider both linear and nonlinear correlations. The filters are constructed in such a way that the obtained correlation values depend on the pose parameters. We show that this dependence is not perfectly linear, in particular for nonlinear correlation. Therefore we use a two-layer neural network to retrieve the pose parameters from the correlation values. We demonstrate the technique by simultaneously estimating the in-plane and out-of-plane orientations of an airplane within an 8-deg portion. We show that a nonlinear correlation is necessary to identify the object and also to estimate its pose. On the other hand, linear correlation is more accurate and more robust. A combination of linear and nonlinear correlations gives the best results.

Phase shifting digital holography implemented with a twisted-nematic liquid-crystal display

We describe and experimentally demonstrate a phase shifting method based on the lateral displacement of a grating implemented with a twisted-nematic liquid-crystal spatial light modulator. This method allows an accurate implementation of the phase shift without requiring moving parts. The technique is implemented in a Mach-Zehnder digital holography setup in which the field transmitted by the sample object freely propagates to the hologram plane.

Phase mask for high focal depth

We present a phase mask that substantially reduces the influence of focus error of an optical system; while preserving light gathering power, and lateral resolution. Numerical simulations and first experimental results are shown.