Combined Adaptive Multiple Subtraction Based on Optimized Event Tracing and Extended Wiener Filtering

The surface-related multiple elimination(SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.

Building Hot Snapshot Copy Based on Windows File System

This paper describes a method for building hot snapshot copy based on windows-file system （HSCF）. The architecture and running mechanism of HSCF are discussed after giving a comparison with other on-line backup tecbnology. HSCF, based on a file system filter driver, protects computer data and ensures their integrity and consistency with following three steps： access to open files, synchronization and copy on-write. Its strategies for improving system performance are analyzed including priority setting, incremental snapshot and load balance. HSCF is a new kind of snapshot technology to solve the data integrity and consistency problem in online backup, which is different from other storage-level snapshot and Open File Solution.

An Enhanced Half Circle Family Window

in this paper,a new window,enhanced half circle family window,is discussed.

基于SWF技术的多曝光图像融合算法

本文提出了一种新的多曝光图像融合算法,该算法结合了导向滤波和SWF(Side Window Filter)技术来保留多曝光图像的细节。该方法主要体现在以下两个方面:一是利用函数关系得到最优滤波半径;其次,利用SWF技术对滤波器进行改进,以保留图像细节;利用输入图像的亮度分量构造混合权值。利用曝光函数对分解后的基层图像和细节层图像进行融合。实验表明,该方法在静态场景下具有较好的融合效果和稳定性。

FIFA-Fast Interpolation and Filtering Algorithm for Calculating Dyadic Green’s Function in the Electromagnetic Scattering of Multi-Layered Structures

The dyadic Green’s function in multi-layer structures for Maxwell equations is a key component for the integral equation method,but time consuming to calculate.A novel algorithm,the Fast Interpolation and Filtering Algorithm(FIFA),for the calculation of the dyadic Green’s function in multi-layer structures is proposed in this paper.We discuss in specific details,ready for use in practical calculations of scattering in layer media,how to apply FIFA to calculate various components of the dyadic Green’s function.The algorithm is based on two techniques:interpolation of Green’s function both in the spectral domain and spatial domain,and low pass filter window based acceleration.Compared to the popular Complex Image Method(CIM),FIFA provides the same speed and overcomes several difficulties associated with CIM while being more general and robust.Specifically,there are no limitations on the frequency range,the number of layers in the structure and the type of Green’s functions to be calculated,and moreover,no need to extract surface wave poles from the spectral form of the Green’s function.Numerical results are given to demonstrate the efficiency and robustness of the proposed method.

Fingerprint Core Location Algorithm Based on Sliding Window

In order to improve the efficiency of the fingerprint core location algorithm, a fingerprint core location method using sliding window on the basis of core location algorithm with the complex filter was proposed. The local region of the fingerprint image was extracted by a fixed-size window sliding in the region of the fingerprint image, and the selected local region by window as the calculation object is used to detect the core. The experiment results show that the method cannot only effectively detect fingerprint core, but also improve the efficiency of the detection algorithm comparing with the global fingerprint core location detection algorithm.

Surface roughness measurement and analysis of mechanical parts based on digital holography

We measure the surface roughness of the mechanical parts based on digital holography. A digital off- axis hologram recording setup for reflective samples is built. Firstly, the height reconstruction error 2.3% of the setup is calibrated by using the quartz step height standard （VLSI- SHS-880QC）. Then, the standard scribed-line model and the grinding roughness specimen are selected as the test samples and their surface roughness are 0.095 6 jam and 0.025 3 jam, with errors 6.3%, 0.9%, respectively. The results are in good agreement with the given roughness parameters. At last, we also analyze the window effect of the filter on the roughness measurement value based on digital holography. In conclu- sion, the paper demonstrated effectively that the digital holography could provide the surface feature for the rough- ness measurement with high accuracy.

SWF-SIFT Approach for Infrared Face Recognition

The scale invariant feature transform （SIFT） feature descriptor is invariant to image scale and location, and is robust to affine transformations and changes in illumination, so it is a powerful descriptor used in many applications, such as object recognition, video tracking, and gesture recognition. However, in noisy and non-rigid object recognition applications, especially for infrared human face recognition, SIFT-based algorithms may mismatch many feature points. This paper presents a star-styled window filter-SIFT （SWF-SIFT） scheme to improve the infrared human face recognition performance by filtering out incorrect matches. Performance comparisons between the SIFT and SWF-SIFT algorithms show the advantages of the SWF-SIFT algorithm through tests using a typical infrared human face database.