Structure image of single crystal of polyethylene

High-resolution electron macroscopic images of lamellar single crystal of polyethylene (PE) have been successfully obtained using high-resolution electron microscopy (HREM), although so far the feasibility of obtaining HREM images from such a radiation sensitive polymer is still drastically questioned. The HREM images with a clear two-dimensional periodic structure reported here were recorded in a transmission electron microscope operated at 200 kV. The images consisted of lattice fringes derived from the <001> zone, and the structure images of different lattice fringes were resolved. To our knowledge, this is the first time that such clear structure images of PE have been reported at a molecular level.

Application of digital image analysis to the study of banded spherulite during growing and melting process

A digital image analysis(DIA) technique can be applied directly to the image obtained by polarizing microscope. The time-resolved DIA apparatus including image collecting, showing and data analysis has been home-made. As an example, it has been used to study the banded spherulite in the blends of poly(epsilon-caprolactone) (PCL) and poly(styrene-ran-acrylonitrile) (SAN).

STM image of tungstosilicic acid molecular layer on highly oriented pyrolytic graphite

Molecular layer of tungstosilicic acid (H4SiW12O40) deposited on freshly-cleaved highly oriented pyrolytic graphite (HOPG) was observed by scanning tunneling microscopy (STM) in air at room temperature. The molecular dimension (11.5 Angstrom) of H4SiW12O40 measured by STM is consistent with known crystallographic parameter. We also imaged the boundary of H4SiW12O40 molecular layer on HOPG showing that molecular layer of H4SiW12O40 was formed. It has been proved that individual tungstosilicic acid species is imaged. The probable reason for the formation of the molecular layer is also discussed.

IN-SITU SCANNING-TUNNELING-MICROSCOPY IMAGE OF A HIGHLY ORIENTED PYROLYTIC-GRAPHITE ELECTRODE MODIFIED WITH POTASSIUM BIS(11-MOLYBDOSILICATO) DYSPROSATE(III) IN SODIUM-SULFATE SOLUTION

The variation in molecule adsorption mode on pretreated highly oriented pyrolytic graphite electrodes, modified with the title complex K10H3[Dy(SiMo11O39)(2)] by cyclic voltammetry in the title complex solution, was observed in situ by electrochemical scanning tunnelling microscopy (ECSTM) with molecular resolution in sodium sulphate solution. According to the ECSTM images and the known molecular structure we conclude that the adsorption mode of the title complex modified electrode changed during potential cycling from ''vertical'' to ''inclined'' and then ''horizontal'' or ''flat'' mode, i.e. the title complex adsorbed on the surface of electrode by one ligand of the complex at first, then began to incline and was finally adsorbed by two ligands of the complex. This result indicates that the adsorption mode on the modified electrode surface changed during potential cycling in the sulphate solution and a much more stable molecular layer was formed. The change in adlattice of adsorbates on the modified electrode surface from hexagonal to rectangular was also observed by ECSTM. A plausible model was given to explain this process.

Spatial and temporal variations of sound speed at the PN section

Gridded sound speed data were calculated using Del Grosso's formulation from the temperature and salinity data at the PN section in the East China Sea covering 92 cruises between February 1978 and October 2000. The vertical gradients of sound speed are mainly related to the seasonal variations, and the strong horizontal gradients are mainly related to the Kuroshio and the upwelling. The standard deviations show that great variations of sound speed exist in the upper layer and in the slope zone. Empirical orthogonal function analysis shows that contributions of surface heating and the Kuroshio to sound speed variance are almost equivalent.

On the nonlinear integral transform of an ocean wave spectrum into an along-track interferometric synthetic aperture radar image spectrum

We present a new nonlinear integral transform relating the ocean wave spectrum to the along-track interferometric synthetic aperture radar (AT-INSAR) image spectrum. The AT-INSAR, which is a synthetic aperture radar (SAR) employing two antennas displaced along the platform's flight direction, is considered to be a better instrument for imaging ocean waves than the SAR. This is because the AT-INSAR yields the phase spectrum and not only the amplitude spectrum as with the conventional SAR. While the SAR and AT-INSAR amplitude spectra depend strongly on the modulation of the normalized radar cross section (NRCS) by the long ocean waves, which is poorly known, the phase spectrum depends only weakly on this modulation. By measuring the phase difference between the signals received by both antennas, AT-INSAR measures the radial component of the orbital velocity associated with the ocean waves, which is related to the ocean wave height field by a well-known transfer function. The nonlinear integral transform derived in this paper differs from the one previously derived by Bao et al. [1999] by an additional term containing the derivative of the radial component of the orbital velocity associated with the long ocean waves. By carrying out numerical simulations, we show that, in general, this additional term cannot be neglected. Furthermore, we present two new quasi-linear approximations to the nonlinear integral transform relating the ocean wave spectrum to the AT-INSAR phase spectrum.

Depth inversion in coastal water based on SAR image of waves

Wave-number spectrum technique is proposed to retrieve coastal water depths by means of Synthetic Aperture Radar (SAR) image of waves. Based on the general dispersion relation of ocean waves, the wavelength changes of a surface wave over varying water depths can be derived from SAR. Approaching the analysis of SAR images of waves and using the general dispersion relation of ocean waves, this indirect technique of remote sensing bathymetry has been applied to a coastal region of Xiapu in Fujian Province, China. Results show that this technique is suitable for the coastal waters especially for the near-shore regions with variable water depths.

Some Extensions of the K-Means Algorithm for Image Segmentation and Pattern Classification

In this paper we present some extensions to the k-means algorithm for vector quantization that permit its efficient use in image segmentation and pattern classification tasks. It is shown that by introducing state variables that correspond to certain statistics of the dynamic behavior of the algorithm, it is possible to find the representative centers fo the lower dimensional maniforlds that define the boundaries between classes, for clouds of multi-dimensional, mult-class data; this permits one, for example, to find class boundaries directly from sparse data (e.g., in image segmentation tasks) or to efficiently place centers for pattern classification (e.g., with local Gaussian classifiers). The same state variables can be used to define algorithms for determining adaptively the optimal number of centers for clouds of data with space-varying density. Some examples of the applicatin of these extensions are also given.

Towards an Example-Based Image Compression Architecture for Video-Conferencing

This paper consists of two major parts. First, we present the outline of a simple approach to very-low bandwidth video-conferencing system relying on an example-based hierarchical image compression scheme. In particular, we discuss the use of example images as a model, the number of required examples, faces as a class of semi-rigid objects, a hierarchical model based on decomposition into different time-scales, and the decomposition of face images into patches of interest. In the second part, we present several algorithms for image processing and animation as well as experimental evaluations. Among the original contributions of this paper is an automatic algorithm for pose estimation and normalization. We also review and compare different algorithms for finding the nearest neighbors in a database for a new input as well as a generalized algorithm for blending patches of interest in order to synthesize new images. Finally, we outline the possible integration of several algorithms to illustrate a simple model-based video-conference system.

Linear Object Classes and Image Synthesis from a Single Example Image

The need to generate new views of a 3D object from a single real image arises in several fields, including graphics and object recognition. While the traditional approach relies on the use of 3D models, we have recently introduced techniques that are applicable under restricted conditions but simpler. The approach exploits image transformations that are specific to the relevant object class and learnable from example views of other "prototypical" objects of the same class. In this paper, we introduce such a new technique by extending the notion of linear class first proposed by Poggio and Vetter. For linear object classes it is shown that linear transformations can be learned exactly from a basis set of 2D prototypical views. We demonstrate the approach on artificial objects and then show preliminary evidence that the technique can effectively "rotate" high- resolution face images from a single 2D view.

Recognition of Surface Reflectance Properties from a Single Image under Unknown Real-World Illumination

This paper describes a machine vision system that classifies reflectance properties of surfaces such as metal, plastic, or paper, under unknown real-world illumination. We demonstrate performance of our algorithm for surfaces of arbitrary geometry. Reflectance estimation under arbitrary omnidirectional illumination proves highly underconstrained. Our reflectance estimation algorithm succeeds by learning relationships between surface reflectance and certain statistics computed from an observed image, which depend on statistical regularities in the spatial structure of real-world illumination. Although the algorithm assumes known geometry, its statistical nature makes it robust to inaccurate geometry estimates.

The Image Dissector "Eyes"

This is a collection of data on the construction operation and performance of the two image dissector cameras. Some of this data is useful in deciding whether certain shortcomings are significant for a given application and if so how to compensate for them.

Recovering Intrinsic Images from a Single Image

We present an algorithm that uses multiple cues to recover shading and reflectance intrinsic images from a single image. Using both color information and a classifier trained to recognize gray-scale patterns, each image derivative is classified as being caused by shading or a change in the surface's reflectance. Generalized Belief Propagation is then used to propagate information from areas where the correct classification is clear to areas where it is ambiguous. We also show results on real images.