Blind image restoration based on the theory of high-dimensional space geometry

In practical situations, the causes of image blurring are often undiscovered or difficult to get known. However, traditional methods usually assume the knowledge of the blur has been known prior to the restoring process, which are not practicable for blind image restoration. A new method proposed in this paper aims exactly at blind image restoration. The restoration process is transformed into a problem of point distribution analysis in high-dimensional space. Experiments have proved that the restoration could be achieved using this method without re-knowledge of the image blur. In addition, the algorithm guarantees to be convergent and has simple computation.

Information geometry theory of high-dimension space and application for speaker independent continuous digit speech recognition

In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.

High-Dimensional Space Geometrical Informatics and its applications to image restoration

With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

A novel image restoration approach based on point location in high-dimensional space geometry

The goal of image restoration is to restore the original clear image from the existing blurred image without distortion as possible. A novel approach based on point location in high-dimensional space geometry method is proposed, which is quite different from the thought ways of existing traditional image restoration approaches. It is based on the high-dimensional space geometry method, which derives from the fact of the Principle of Homology-Continuity (PHC). Begin with the original blurred image, we get two further blurred images. Through the regressive deducing curve fitted by these three images, the first iterative deblured image could be obtained. This iterative "blurring-debluring-blurring" process is performed till reach the deblured image. Experiments have proved the availability of the proposed approach and achieved not only common image restoration but also blind image restoration which represents the majority of real problems.

A face detection algorithm based on high dimensional space geometry

In this paper, a face detection algorithm which is based on high dimensional space geometry has been proposed. Then after the simulation experiment of Euclidean Distance and the introduced algorithm, it was theoretically analyzed and discussed that the proposed algorithm has apparently advantage over the Euclidean Distance. Furthermore, in our experiments in color images, the proposed algorithm even gives more surprises.

An algorithm of analysis tools on points distribution in high dimension space: The distance of a point and an infinite sub-space

This paper discusses the algorithm on the distance from a point and an infinite sub-space in high dimensional space With the development of Information Geometry([1]), the analysis tools of points distribution in high dimension space, as a measure of calculability, draw more attention of experts of pattern recognition. By the assistance of these tools, Geometrical properties of sets of samples in high-dimensional structures are studied, under guidance of the established properties and theorems in high-dimensional geometry.

High-Dimensional Space Geometrical Informatics and its applications to image restoration

With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

A Novel Geometric Algorithm for Blind Image Restoration Based on High-Dimensional Space

A novel geometric algorithm for blind image restoration is proposed in this paper, based on High-Dimensional Space Geometrical Informatics (HDSGI) theory. In this algorithm every image is considered as a point, and the location relationship of the points in high-dimensional space, i.e. the intrinsic relationship of images is analyzed. Then geometric technique of "blurring-blurring-deblurring" is adopted to get the deblurring images. Comparing with other existing algorithms like Wiener filter, super resolution image restoration etc., the experimental results show that the proposed algorithm could not only obtain better details of images but also reduces the computational complexity with less computing time. The novel algorithm probably shows a new direction for blind image restoration with promising perspective of applications.

One-dimensional modulation instability of broad optical beams in biased photorefractive-photovoltaic crystals under steady-state conditions

We present a comprehensive study of the one-dimensional modulation instability of broad optical beams in biased photo refractive-photovoltaic crystals under steady-state conditions. We obtain the one-dimensional modulation instability growth rate by globally treating the space-charge field and by considering distinction between values of Eo in nonlocal effects and local effects in the space-charge field, where Eo is the field constant correlated with terms in the space-charge field, which depends on the external bias field, the bulk photovoltaic effect, and the ratio of the optical beam's intensity to that of the dark irradiance. The one-dimensional modulation instability growth rate in local effects can be determined from that in nonlocal effects. When the bulk photovoltaic effect is neglectable, irrespective of distinction between values of Eo in nonlocal effects and local effects in the space-charge field, the one-dimensional modulation instability growth rates in nonlocal effects and local effects are those of broad optical beams studied previously in biased photorefractive-nonphotovoltaic crystals. When the external bias field is absent, the one-dimensional modulation instability growth rates in nonlocal effects and local effects predict those of broad optical beams in open- and closed-circuit photorefractive-photovoltaic crystals. (c) 2004 Elsevier B.V. All rights reserved.

Modulation instability of quasi-plane-wave optical beams in biased photorefractive-photovoltaic crystals

We investigate the modulation instability of quasi-plane-wave optical beams in biased photorefractive-photovoltaic crystals by globally treating the space-charge field. The modulation instability growth rate is obtained, which depends on the external bias field, on the bulk photovoltaic effect, and on the ratio of the optical beam's intensity to that of the dark irradiance. Our analysis indicates that this modulation instability growth rate is identical to the modulation instability growth rate studied previously in biased photorefractive-nonphotovoltaic crystals when the bulk photovoltaic effect is negligible for shorted circuits, and predicts the modulation instability growth rate in open- and closed-circuit photorefractive-photovoltaic crystals when the external bias field is absent.

A new method for spectrum reproduction and interferogram processing

On the basis of researchon the theory and mathe matics of interference data collection of the spatially modulated polarization interference imaging spectrometer designed by us, this paper mainly analyses and compares three different methods of spectrum reconstruction and interferogram processing. Specially, the authors introduce the nonparametric model of Music algorithm which is maturely used in power spectrum estimation into the spectrum reconstruction processing for the first time. This method prodigiously improves the resolution of reproduced spectrum, and provides a better math matic model for the improvement of resolving power in spectrum reproduction.

NEW FORMATION MECHANISM OF ELECTRIC-FIELD DOMAIN DUE TO GAMMA-X SEQUENTIAL TUNNELING IN GAAS/ALAS SUPERLATTICES

We have studied the sequential tunneling of doped weakly coupled GaAs/ALAs superlattices (SLs), whose ground state of the X valley in AlAS layers is designed to be located between the ground state (E(GAMMA1)) and the first excited state (E(GAMMA2)) of the GAMMA valley in GaAs wells. The experimental results demonstrate that the high electric field domain in these SLs is attributed to the GAMMA-X sequential tunneling instead of the usual sequential resonant tunneling between subbands in adjacent wells. Within this kind of high field domain, electrons from the ground state in the GaAs well tunnel to the ground state of the X valley in the nearest AlAs layer, then through very rapid real-space transfer relax from the X valley in the AlAs layer to the ground state of the GAMMA valley of the next GaAs well.

Biomimetic (topological) pattern recognition - A new model of pattern recognition theory and its application

A new theoretical model of Pattern Recognition principles was proposed, which is based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition. This new model is closer to the function of human being, rather than traditional statistical Pattern Recognition using "optimal separating" as its main principle. So the new model of Pattern Recognition is called the Biomimetic Pattern Recognition (BPR)(1). Its mathematical basis is placed on topological analysis of the sample set in the high dimensional feature space. Therefore, it is also called the Topological Pattern Recognition (TPR). The fundamental idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples. We experimented with the Biomimetic Pattern Recognition (BPR) by using artificial neural networks, which act through covering the high dimensional geometrical distribution of the sample set in the feature space. Onmidirectionally cognitive tests were done on various kinds of animal and vehicle models of rather similar shapes. For the total 8800 tests, the correct recognition rate is 99.87%. The rejection rate is 0.13% and on the condition of zero error rates, the correct rate of BPR was much better than that of RBF-SVM.

Space-grown SI-GaAs and its application

A semi-insulating GaAs single crystal ingot was grown in a recoverable satellite, within a specially designed pyrolytic boron nitride crucible, in a power-travelling furnace under microgravity. The crystal was characterized systematically and was used in fabricating low noise field effect transistors and analogue switch integrated circuits by the direct ion-implantation technique. All key electrical properties of these transistors and integrated circuits have surpassed those made from conventional earth-grown gallium arsenide. This result shows that device-grade space-grown semiconducting single. crystal has surpassed the best. terrestrial counterparts. Studies on the correlation between SI-GaAs wafers and the electronic devices and integrated circuits indicate that the characteristics of a compound semiconductor single crystal depends fundamentally on its stoichiometry.

Observation of N-Shaped Negative Differential Resistance in GaAs-Based Modulation-Doped Field Effect Transistor with InAs Quantum Dots

N-shaped negative differential resistance (NDR) with a high peak-to-valley ratio (PVR) is observed in a GaAs-based modulation-doped field effect transistor (MODFET) with InAs quantum dots (QDs) in the barrier layer (QDFET) compared with a GaAs MODFET. The NDR is explained as the real-space transfer (RST) of high-mobility electrons in a channel into nearby barrier layers with low mobility, and the PVR is enhanced dramatically upon inserting the QD layer. It is also revealed that the QD layer traps holes and acts as a positively charged nano-floating gate after a brief optical illumination, while it acts as a negatively charged nano-floating gate and depletes the adjacent channel when charged by the electrons. The NDR suggests a promising application in memory or high-speed logic devices for the QDFET structure.