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 global shallow water model using high order multi-moment constrained finite volume method and icosahedral grid

A novel accurate numerical model for shallow water equations on sphere have been developed by implementing the high order multi-moment constrained finite volume (MCV) method on the icosahedral geodesic grid. High order reconstructions are conducted cell-wisely by making use of the point values as the unknowns distributed within each triangular cell element. The time evolution equations to update the unknowns are derived from a set of constrained conditions for two types of moments, i.e. the point values on the cell boundary edges and the cell-integrated average. The numerical conservation is rigorously guaranteed. in the present model, all unknowns or computational variables are point values and no numerical quadrature is involved, which particularly benefits the computational accuracy and efficiency in handling the spherical geometry, such as coordinate transformation and curved surface. Numerical formulations of third and fourth order accuracy are presented in detail. The proposed numerical model has been validated by widely used benchmark tests and competitive results are obtained. The present numerical framework provides a promising and practical base for further development of atmospheric and oceanic general circulation models. (C) 2009 Elsevier Inc. All rights reserved.

Measurement of neutron-removal cross section of neutron-rich nucleus He-8 by using the transmission method

The neutron-rich nucleus He-8 is selected by RIBLL from the breakup of 50MeV/u C-13 on be target at HIRFL. The 2n-removal and 4n-removal cross section of He-8 was measured by using the transmission method. The point that He-4 is He-8 core can be reduced from the experiment data via the Ogawa's theory.

Comparison of salt titration and potentiometric titration methods for the determination of zero point of charge

the salt ritration metod was evaluated as a method to determine zpc in comparison with the potentiometric titration method for 26 soil with variable charge clays,i.e.,Oxisols and Ultisols from Thailand and Andisols from Japan. In addition to the determination of ST-pH0 as the zero point of charge, a calculation procedure was adopted here in order to acquire more information from the titration curve . fuithermore, for the purpose of cross-checking of zpc determined by the pt method, the st procedure was successively applied to the samples analyzed by the pt method.

DECODE: a new method for discovering clusters of different densities in spatial data

National Key Basic Research and Development Program of China [2006CB701305]; State Key Laboratory of Resource and Environment Information System [088RA400SA]; Chinese Academy of Sciences

Study of self-assembly of symmetric coil-rod-coil ABA-type triblock copolymers by self-consistent field lattice method

The self-assembly of symmetric coil-rod-coil ABA-type triblock copolymer melts is studied by applying self-consistent field lattice techniques in a three-dimensional space. The self-assembled ordered structures differ significantly with the variation of the volume fraction of the rod component, which include lamellar, wave lamellar, gyroid, perforated lamellar, cylindrical, and spherical-like phases. To understand the physical essence of these phases and the regimes of occurrence, we construct the phase diagram, which matches qualitatively with the existing experimental results. Compared with the coil-rod AB diblock copolymer, our results revealed that the interfacial grafting density of the separating rod and coil segments shows important influence on the self-assembly behaviors of symmetric coil-rod-coil ABA triblock copolymer melts. We found that the order-disorder transition point changes from f(rod)=0.5 for AB diblock copolymers to f(rod)=0.6 for ABA triblock copolymers. Our results also show that the spherical-like and cylindrical phases occupy most of the region in the phase diagram, and the lamellar phase is found stable only at the high volume fraction of the rod.

Joint statistical distribution of two-point sea surface elevations in finite water depth

Based on the second-order random wave solutions of water wave equations in finite water depth, a joint statistical distribution of two-point sea surface elevations is derived by using the characteristic function expansion method. It is found that the joint distribution depends on five parameters. These five parameters can all be determined by the water depth, the relative position of two points and the wave-number spectrum of ocean waves. As an illustrative example, for fully developed wind-generated sea, the parameters that appeared in the joint distribution are calculated for various wind speeds, water depths and relative positions of two points by using the Donelan and Pierson spectrum and the nonlinear effects of sea waves on the joint distribution are studied. (C) 2003 Elsevier B.V. All rights reserved.

A QUASI-SIMPLEX METHOD FOR STRICTLY CONVEX QUADRATIC PROGRAMMING

本文提出一个不用 Kuhn- Tucker条件而直接搜索严格凸二次规划最优目标点的鲁棒方法 .在搜索过程中 ,目标点沿约束多面体边界上的一条折线移动 .这种移动目标点的思想可以被认为是线性规划单纯形法的自然推广 ,在单纯形法中 ,目标点从一个顶点移到另一个顶点。

Shape from Shading: A Method for Obtaining the Shape of a Smooth Opaque Object from One View

A method will be described for finding the shape of a smooth apaque object form a monocular image, given a knowledge of the surface photometry, the position of the lightsource and certain auxiliary information to resolve ambiguities. This method is complementary to the use of stereoscopy which relies on matching up sharp detail and will fail on smooth objects. Until now the image processing of single views has been restricted to objects which can meaningfully be considered two-dimensional or bounded by plane surfaces. It is possible to derive a first-order non-linear partial differential equation in two unknowns relating the intensity at the image points to the shape of the objects. This equation can be solved by means of an equivalent set of five ordinary differential equations. A curve traced out by solving this set of equations for one set of starting values is called a characteristic strip. Starting one of these strips from each point on some initial curve will produce the whole solution surface. The initial curves can usually be constructed around so-called singular points. A number of applications of this metod will be discussed including one to lunar topography and one to the scanning electron microscope. In both of these cases great simplifications occur in the equations. A note on polyhedra follows and a quantitative theory of facial make-up is touched upon. An implementation of some of these ideas on the PDP-6 computer with its attached image-dissector camera at the Artificial intelligence Laboratory will be described, and also a nose-recognition program.

Automatic point correspondence and registration based on linear structures

R. Marti, R. Zwiggelaar, C.M.E. Rubin, 'Automatic point correspondence and registration based on linear structures', International Journal of Pattern Recognition and Artificial Intelligence 16 (3), 331-340 (2002)

Making Sadza with Deaf Zimbabwean Women: A Missiological Reorientation of Practical Theological Method toward Self-Theologizing Agency among Subaltern Communities

Missiological calls for self-theologizing among faith communities present the field of practical theology with a challenge to develop methodological approaches that address the complexities of cross-cultural, practical theological research. Although a variety of approaches can be considered critical correlative practical theology, existing methods are often built on assumptions that limit their use in subaltern contexts. This study seeks to address these concerns by analyzing existing theological methodologies with sustained attention to a community of Deaf Zimbabwean women struggling to develop their own agency in relation to child rearing practices. This dilemma serves as an entry point to an examination of the limitations of existing methodologies and a constructive, interdisciplinary theological exploration. The use of theological modeling methodology employs my experience of learning to cook sadza, a staple dish of Zimbabwe, as a guide for analyzing and reorienting practical theological methodology. The study explores a variety of theological approaches from practical theology, mission oriented theologians, theology among Deaf communities, and African women’s theology in relationship to the challenges presented by subaltern communities such as Deaf Zimbabwean women. Analysis reveals that although there is much to commend in these existing methodologies, questions about who does the critical correlation, whose interests are guiding the study, and consideration for the cross-cultural and power dynamics between researchers and faith communities remain problematic for developing self-theologizing agency. Rather than frame a comprehensive methodology, this study proposes three attitudes and guideposts to reorient practical theological researchers who wish to engender self-theologizing agency in subaltern communities. The creativity of enacted theology, the humility of using checks and balances in research methods, and the grace of finding strategies to build bridges of commonality and community offer ways to reorient practical theological methodologies toward the development of self-theologizing agency among subaltern people. This study concludes with discussion of how these guideposts can not only benefit particular work with a community of Deaf Zimbabwean women, but also provide research and theological reflection in other subaltern contexts.

Surface-electrode point Paul trap

We present a model as well as experimental results for a surface electrode radiofrequency Paul trap that has a circular electrode geometry well suited for trapping single ions and two-dimensional planar ion crystals. The trap design is compatible with microfabrication and offers a simple method by which the height of the trapped ions above the surface may be changed in situ. We demonstrate trapping of single Sr88+ ions over an ion height range of 200-1000 μm for several hours under Doppler laser cooling and use these to characterize the trap, finding good agreement with our model. © 2010 The American Physical Society.

Recognition of Planar Segments in Point Cloud Based on Wavelet Transform

© 2005-2012 IEEE.Within industrial automation systems, three-dimensional (3-D) vision provides very useful feedback information in autonomous operation of various manufacturing equipment (e.g., industrial robots, material handling devices, assembly systems, and machine tools). The hardware performance in contemporary 3-D scanning devices is suitable for online utilization. However, the bottleneck is the lack of real-time algorithms for recognition of geometric primitives (e.g., planes and natural quadrics) from a scanned point cloud. One of the most important and the most frequent geometric primitive in various engineering tasks is plane. In this paper, we propose a new fast one-pass algorithm for recognition (segmentation and fitting) of planar segments from a point cloud. To effectively segment planar regions, we exploit the orthonormality of certain wavelets to polynomial function, as well as their sensitivity to abrupt changes. After segmentation of planar regions, we estimate the parameters of corresponding planes using standard fitting procedures. For point cloud structuring, a z-buffer algorithm with mesh triangles representation in barycentric coordinates is employed. The proposed recognition method is tested and experimentally validated in several real-world case studies.

Micro-Anatomical Quantitative Imaging Towards Enabling Automated Diagnosis of Thick Tissues at the Point of Care

Histopathology is the clinical standard for tissue diagnosis. However, histopathology has several limitations including that it requires tissue processing, which can take 30 minutes or more, and requires a highly trained pathologist to diagnose the tissue. Additionally, the diagnosis is qualitative, and the lack of quantitation leads to possible observer-specific diagnosis. Taken together, it is difficult to diagnose tissue at the point of care using histopathology.

Several clinical situations could benefit from more rapid and automated histological processing, which could reduce the time and the number of steps required between obtaining a fresh tissue specimen and rendering a diagnosis. For example, there is need for rapid detection of residual cancer on the surface of tumor resection specimens during excisional surgeries, which is known as intraoperative tumor margin assessment. Additionally, rapid assessment of biopsy specimens at the point-of-care could enable clinicians to confirm that a suspicious lesion is successfully sampled, thus preventing an unnecessary repeat biopsy procedure. Rapid and low cost histological processing could also be potentially useful in settings lacking the human resources and equipment necessary to perform standard histologic assessment. Lastly, automated interpretation of tissue samples could potentially reduce inter-observer error, particularly in the diagnosis of borderline lesions.

To address these needs, high quality microscopic images of the tissue must be obtained in rapid timeframes, in order for a pathologic assessment to be useful for guiding the intervention. Optical microscopy is a powerful technique to obtain high-resolution images of tissue morphology in real-time at the point of care, without the need for tissue processing. In particular, a number of groups have combined fluorescence microscopy with vital fluorescent stains to visualize micro-anatomical features of thick (i.e. unsectioned or unprocessed) tissue. However, robust methods for segmentation and quantitative analysis of heterogeneous images are essential to enable automated diagnosis. Thus, the goal of this work was to obtain high resolution imaging of tissue morphology through employing fluorescence microscopy and vital fluorescent stains and to develop a quantitative strategy to segment and quantify tissue features in heterogeneous images, such as nuclei and the surrounding stroma, which will enable automated diagnosis of thick tissues.

To achieve these goals, three specific aims were proposed. The first aim was to develop an image processing method that can differentiate nuclei from background tissue heterogeneity and enable automated diagnosis of thick tissue at the point of care. A computational technique called sparse component analysis (SCA) was adapted to isolate features of interest, such as nuclei, from the background. SCA has been used previously in the image processing community for image compression, enhancement, and restoration, but has never been applied to separate distinct tissue types in a heterogeneous image. In combination with a high resolution fluorescence microendoscope (HRME) and a contrast agent acriflavine, the utility of this technique was demonstrated through imaging preclinical sarcoma tumor margins. Acriflavine localizes to the nuclei of cells where it reversibly associates with RNA and DNA. Additionally, acriflavine shows some affinity for collagen and muscle. SCA was adapted to isolate acriflavine positive features or APFs (which correspond to RNA and DNA) from background tissue heterogeneity. The circle transform (CT) was applied to the SCA output to quantify the size and density of overlapping APFs. The sensitivity of the SCA+CT approach to variations in APF size, density and background heterogeneity was demonstrated through simulations. Specifically, SCA+CT achieved the lowest errors for higher contrast ratios and larger APF sizes. When applied to tissue images of excised sarcoma margins, SCA+CT correctly isolated APFs and showed consistently increased density in tumor and tumor + muscle images compared to images containing muscle. Next, variables were quantified from images of resected primary sarcomas and used to optimize a multivariate model. The sensitivity and specificity for differentiating positive from negative ex vivo resected tumor margins was 82% and 75%. The utility of this approach was further tested by imaging the in vivo tumor cavities from 34 mice after resection of a sarcoma with local recurrence as a bench mark. When applied prospectively to images from the tumor cavity, the sensitivity and specificity for differentiating local recurrence was 78% and 82%. The results indicate that SCA+CT can accurately delineate APFs in heterogeneous tissue, which is essential to enable automated and rapid surveillance of tissue pathology.

Two primary challenges were identified in the work in aim 1. First, while SCA can be used to isolate features, such as APFs, from heterogeneous images, its performance is limited by the contrast between APFs and the background. Second, while it is feasible to create mosaics by scanning a sarcoma tumor bed in a mouse, which is on the order of 3-7 mm in any one dimension, it is not feasible to evaluate an entire human surgical margin. Thus, improvements to the microscopic imaging system were made to (1) improve image contrast through rejecting out-of-focus background fluorescence and to (2) increase the field of view (FOV) while maintaining the sub-cellular resolution needed for delineation of nuclei. To address these challenges, a technique called structured illumination microscopy (SIM) was employed in which the entire FOV is illuminated with a defined spatial pattern rather than scanning a focal spot, such as in confocal microscopy.

Thus, the second aim was to improve image contrast and increase the FOV through employing wide-field, non-contact structured illumination microscopy and optimize the segmentation algorithm for new imaging modality. Both image contrast and FOV were increased through the development of a wide-field fluorescence SIM system. Clear improvement in image contrast was seen in structured illumination images compared to uniform illumination images. Additionally, the FOV is over 13X larger than the fluorescence microendoscope used in aim 1. Initial segmentation results of SIM images revealed that SCA is unable to segment large numbers of APFs in the tumor images. Because the FOV of the SIM system is over 13X larger than the FOV of the fluorescence microendoscope, dense collections of APFs commonly seen in tumor images could no longer be sparsely represented, and the fundamental sparsity assumption associated with SCA was no longer met. Thus, an algorithm called maximally stable extremal regions (MSER) was investigated as an alternative approach for APF segmentation in SIM images. MSER was able to accurately segment large numbers of APFs in SIM images of tumor tissue. In addition to optimizing MSER for SIM image segmentation, an optimal frequency of the illumination pattern used in SIM was carefully selected because the image signal to noise ratio (SNR) is dependent on the grid frequency. A grid frequency of 31.7 mm-1 led to the highest SNR and lowest percent error associated with MSER segmentation.

Once MSER was optimized for SIM image segmentation and the optimal grid frequency was selected, a quantitative model was developed to diagnose mouse sarcoma tumor margins that were imaged ex vivo with SIM. Tumor margins were stained with acridine orange (AO) in aim 2 because AO was found to stain the sarcoma tissue more brightly than acriflavine. Both acriflavine and AO are intravital dyes, which have been shown to stain nuclei, skeletal muscle, and collagenous stroma. A tissue-type classification model was developed to differentiate localized regions (75x75 µm) of tumor from skeletal muscle and adipose tissue based on the MSER segmentation output. Specifically, a logistic regression model was used to classify each localized region. The logistic regression model yielded an output in terms of probability (0-100%) that tumor was located within each 75x75 µm region. The model performance was tested using a receiver operator characteristic (ROC) curve analysis that revealed 77% sensitivity and 81% specificity. For margin classification, the whole margin image was divided into localized regions and this tissue-type classification model was applied. In a subset of 6 margins (3 negative, 3 positive), it was shown that with a tumor probability threshold of 50%, 8% of all regions from negative margins exceeded this threshold, while over 17% of all regions exceeded the threshold in the positive margins. Thus, 8% of regions in negative margins were considered false positives. These false positive regions are likely due to the high density of APFs present in normal tissues, which clearly demonstrates a challenge in implementing this automatic algorithm based on AO staining alone.

Thus, the third aim was to improve the specificity of the diagnostic model through leveraging other sources of contrast. Modifications were made to the SIM system to enable fluorescence imaging at a variety of wavelengths. Specifically, the SIM system was modified to enabling imaging of red fluorescent protein (RFP) expressing sarcomas, which were used to delineate the location of tumor cells within each image. Initial analysis of AO stained panels confirmed that there was room for improvement in tumor detection, particularly in regards to false positive regions that were negative for RFP. One approach for improving the specificity of the diagnostic model was to investigate using a fluorophore that was more specific to staining tumor. Specifically, tetracycline was selected because it appeared to specifically stain freshly excised tumor tissue in a matter of minutes, and was non-toxic and stable in solution. Results indicated that tetracycline staining has promise for increasing the specificity of tumor detection in SIM images of a preclinical sarcoma model and further investigation is warranted.

In conclusion, this work presents the development of a combination of tools that is capable of automated segmentation and quantification of micro-anatomical images of thick tissue. When compared to the fluorescence microendoscope, wide-field multispectral fluorescence SIM imaging provided improved image contrast, a larger FOV with comparable resolution, and the ability to image a variety of fluorophores. MSER was an appropriate and rapid approach to segment dense collections of APFs from wide-field SIM images. Variables that reflect the morphology of the tissue, such as the density, size, and shape of nuclei and nucleoli, can be used to automatically diagnose SIM images. The clinical utility of SIM imaging and MSER segmentation to detect microscopic residual disease has been demonstrated by imaging excised preclinical sarcoma margins. Ultimately, this work demonstrates that fluorescence imaging of tissue micro-anatomy combined with a specialized algorithm for delineation and quantification of features is a means for rapid, non-destructive and automated detection of microscopic disease, which could improve cancer management in a variety of clinical scenarios.

Metocean Comparisons of Jason-2 and AltiKa—A Method to Develop a New Wind Speed Algorithm

As well as range, the AltiKa altimeter provides estimates of wave height, Hs and normalized backscatter, s0, that need to be assessed prior to statistics based on them being included in climate databases. An analysis of crossovers with the Jason-2 altimeter shows AltiKa Hs values to be biased high by only »0.05m, with a standard deviation (s.d.) of »0.1m for seven-point averages. AltiKa’s s 0 values are 2.5–3 dB less than those from Jason-2, with a s.d. of »0.3 dB, with these relatively large mismatches to be expected as AltiKa measures a different part of the spectrum of sea surface roughness. A new wind speed algorithm is developed through matchinghistogram of s0 values to that for Jason-2 wind speeds. The algorithm is robust to the use of short durations of data, with a consistency at roughly the 0.1 m/s level. Incorporation of Hs as a secondary input reduces the assessed error at crossovers from 0.82 m/s to 0.71 m/s. A comparison across all altimeter frequencies used to date demonstrates that the lowest wind speeds preferentially develop the shortest scales of roughness.