Fast regularized image interpolation method

The regularized image interpolation method is widely used based on the vector interpolation model in which down-sampling matrix has very large dimension and needs large storage consumption and higher computation complexity. In this paper, a fast algorithm for image interpolation based on the tensor product of matrices is presented, which transforms the vector interpolation model to matrix form. The proposed algorithm can extremely reduce the storage requirement and time consumption. The simulation results verify their validity.

Simulation of an apodizer's effect for high-density optical storage

The effect of an apodizer with two parallel taper refractive surfaces is theoretically investigated for highdensity optical storage. The apodizer may modulate an incident Gaussian beam into an annular beam. Simulation shows that with the increasing inner radius of the modulated beam, the focal spot shrinks obviously. The depolarization effect gets strong simultaneously, which induces the circular symmetry loss of the focal spot. In this process, pattern density of the orthogonal and longitudinal diffractive fields increases remarkably.

Design and performance of a video-based laser beam automatic alignment system

A laser alignment system is applied to a high power laser facility for inertial confinement fusion. A design of the automated, close-loop laser beam alignment system is described. Its function is to sense beam alignment errors in a laser beam transport system and automatically steer mirrors preceding the sensor location as required to maintain beam alignment. The laser beam is sampled by a sensor package, which uses video cameras to sense pointing and centering errors. The camera outputs are fed to a personal computer, which includes video digitizers and uses image storage and software to sense the centroid of the image. Signals are sent through the computer to a stepper motor controller, which drives stepper motors on mirror mounts preceding the beam sampling location to return the beam alignment to the prescribed condition. Its optical principles and key techniques are given. The pointing and centering sensitivities of the beam alignment sensor package are analyzed. The system has been verified on the

Real-time phase-shift ing techniques for determining the photoelastic parameters: a theoretical comparison

Among data acquisition techniques in digital photoelasticity, the integrated phase shifting technique (IPST) can real-time analyze the photoelastic parameters at a video rate of the high speed CCD camera. In this paper, fourteen algorithms are described by different configurations of the rotating an analyzer at a constant rate and an output quarter-wave plate at another constant rate. The theoretical comparisons of the algorithms are given by the simulated phase distributions of the isochromatic and isoclinic parameters of the disk under two cases that the load keeps unchangeable or linearly increasing in exposure time of the camera. Then a guideline is given to alleviate the influence of the load changing with time on the IPST.

Sub-pixel processing algorithm of the reducing boundary recursive error in staring FPA micro-scanning imaging

By analyzing the error distribution rule of the boundary recursive reconstruction algorithm in controlled micro-scanning, a sub-pixel image processing algorithm is proposed to reduce the error. The gray statistical principle is used in the algorithm to optimize the error and acquire the sub-pixel image that approximates the originM image. The simulation result shows that the effect of this algorithm is better than the over- sample and simple boundary recursive algorithm （BRA）, and it results in a good effect both in those of visible light and infrared imaging systems. Therefore, the application of this algorithm will enhance the performance of optoelectronic imaging systems.

Robust color segmentation algorithms in illumination variation conditions

Changing illumination condition can change the result of image segmentation algorithm and reduce the intelligent recognition rate. A novel color image segmentation method robust to illumination variations is presented. The method is applied to the skin segmentation. Based on the hue preserving algorithm, the method reduces the dimensionality of the red-green-blue （RGB） space to one dimension, while keeping the hue of every pixel unchanging before and after space transformation. In the new color space, the skin color model is established using Gaussian model. Experimental results show that the method is robust to illumination variations, and has low computational complexity.