Adaptive Window Based 3-D Feature Selection for Multispectral Image Classification Using Firefly Algorithm

Feature extraction is the most critical step in classification of multispectral image.The classification accuracy is mainly influenced by the feature sets that are selected to classify the image.In the past,handcrafted feature sets are used which are not adaptive for different image domains.To overcome this,an evolu-tionary learning method is developed to automatically learn the spatial-spectral features for classification.A modified Firefly Algorithm(FA)which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose.For extracting the most effi-cient features from the data set,we have used 3-D discrete wavelet transform which decompose the multispectral image in all three dimensions.For selecting spatial and spectral features we have studied three different approaches namely overlapping window(OW-3DFS),non-overlapping window(NW-3DFS)adaptive window cube(AW-3DFS)and Pixel based technique.Fivefold Multiclass Support Vector Machine(MSVM)is used for classification purpose.Experiments con-ducted on Madurai LISS IV multispectral image exploited that the adaptive win-dow approach is used to increase the classification accuracy.

The Parameter Determination in the Design of 3-D Spherically Symmetric FIR Filters via the McClellan Transformation

In the design of 3-D spherically symmetric FIR filters via the McClellan transformation, two methods are proposed to determine the transformation parameters. The first is to improve the original 3-D algorithm by exploiting the 2-D effective methods in 3-D. This method can change the constrained optimization algorithm into the unconstrained one and makes the design easier to realize. The second method is to solve the coupled equations under constrained conditions and a set of ideal parameters can be gotten. The design example shows that the two methods are all efficient and easier than the original algorithm.

Motion Planning System for Bin Picking Using 3-D Point Cloud

In this paper, we propose a motion planning system for bin picking using 3-D point cloud. The situation that the objects are put miscellaneously like the inside in a house is assumed. In the home, the equipment which makes an object stand in line doesn’t exist. Therefore the motion planning system which considered a collision problem becomes important. In this paper, Information on the objects is measured by a laser range finder (LRF). The information is used as 3-D point cloud, and the objects are recognized by model-base. We propose search method of a grasping point for two-fingered robotic hand, and propose search method of a path to approach the grasping point without colliding with other objects.

Determination of 3-D Velocity Anomalies of the Nanbei Tectonic Zone of China Based on Local Earthquakes

In this paper, 3-D velocity images of the crust and upper mantle beneath the Nanbei tectonic zone of China are constructed using P-wave travel time residuals of earthquakes, with the data supplied by China's seismic networks and the International Seismic Centre.

基于拓扑结构不变性的3D并行细化算法及其应用

目的双距离场算法提取的骨架居中性不佳,并且算法复杂度高,实时性差。本文提出一种基于拓扑结构不变性的3D细化算法以提取肺气管的骨架。方法首先介绍了基于双距离场和拓扑结构不变性两种算法的基本原理,然后通过对欧拉特性不变性的证明,利用欧拉特性表查询来计算欧拉值,并计算26临域的连通度。利用欧拉特性值和连通度来保证拓扑结构,定义了一种拓扑结构不变的简单点,用并行的细化策略,快速获取单像素宽、连通的骨架中心线。结果将此算法应用于肺气管快速提取骨架中心线,利用已经分割出的高精度肺部气道树来提取骨架中心线。结论基于拓扑结构不变性的3D并行细化算法与基于距离场的骨架提取算法相比得到更光滑、居中性更好的骨架,并且鲁棒性好,对噪声不敏感。

Three-Dimensional Interferometric ISAR Sensors Imaging for the Ship Target with Two-Dimensional Sparsity

There are great challenges for traditional three-dimensional( 3-D) interferometric inverse synthetic aperture radar( In ISAR) imaging algorithms of ship targets w ith 2-D sparsity in actual radar imaging system. To deal w ith this problem,a novel 3-D In ISAR imaging method is proposed in this paper.First,the high-precision gradient adaptive algorithm w as adopted to reconstruct the echoes in range dimension. Then the method of minimizing the entropy of the average range profile w as applied to estimate the parameters w hich are used to compensate translation components of the received echoes. Besides,the phase adjustment and image coregistration of the sparse echoes w ere achieved at the same time through the approach of the joint phase autofocus. Finally,the 3-D geometry coordinates of the ship target w ith 2-D sparsity w ere reconstructed by combining the range measurement and interferometric processing of the ISAR images. Simulation experiments w ere carried out to verify the practicability and effectiveness of the algorithm in the case that the received echoes are in 2-D sparsity.

线结构光图像骨架的剪枝算法

在采用线结构光进行三维测量的过程中,将光刀图像细化后得到的骨架会出现许多毛刺和分枝,而光刀图像骨架的位置和形状将会直接影响到测量的精度,为了能够得到一条光顺并具有单一连通性的骨架,必须对其进行剪枝处理。为此提出了一种基于曲线追踪技术的剪枝算法,在分枝点处,根据光刀主干的走向找出分枝,从而快速有效的将这些分枝剔除,使最后得到的线条满足骨架的要求。实验表明,这种方法能有效地剪掉分支和消除伪特征,有利于最后三维重建的数据处理。

Synthetic aperture radar tomography sampling criteria and three-dimensional range migration algorithm with elevation digital spotlighting

Based on the general geometric model of multi-baseline Synthetic Aperture Radar Tomography （TomoSAR）, the three-dimensional （3-D） sampling criteria, the analytic expression of the 3-D Point Spread Function （PSF） and the 3-D resolution are derived in the 3-D wavenumber domain in this paper. Considering the relationship between the observation geometry and the size of illuminated scenario, a 3-D Range Migration Algorithm with Elevation Digital Spotlighting （RMA-EDS） is proposed. With this algorithm 3-D images of the area of interest can be directly and accurately reconstructed in the 3-D space avoiding the complex operations of 3-D geometric correction. Finally, theoretical analyses and simulation results are presented to demonstrate the shift-varying property of the 3-D PSF and the spatialvarying property of the 3-D resolution and to demonstrate the validity of the 3-D RMA-EDS.

A NONOVERLAPPING DOMAIN DECOMPOSITION METHOD FOR EXTERIOR 3-D PROBLEM

Examines a nonoverlapping domain decomposition method based on the natural boundary reduction. Development of the D-N alternating algorithm; Studies the convergence of the D-N method for exterior spherical domain; Discussion of the discrete form of the D-N alternating algorithm.

A High Speed Detection Scheme for Point Targets in a Multitarget Environment

The purpose of this paper is to develop a high speed detection scheme for moving and / or stationary point targets in a multitarget environment as registered in an IR image sequence. An iterative approximate 3-D line searching algorithm based upon the geometric representation of lines (for non-maneuvering targets in space) in a 3-D space is derived. The convergency of the algorithm is proved. An analysis is performed of the theoretical detection performance of the algorithm. The statistical experiment results show high effectiveness and computational efficiency of the algorithm in the case of low SNR. The idea may be employed to satisfy the real-time processing requirement of an IR system.

Three-dimensional cooperative guidance laws against stationary and maneuvering targets

This paper presents the cooperative strategies for salvo attack of multiple missiles based on the classical proportional navigation（PN） algorithm.The three-dimensional（3-D） guidance laws are developed in a quite simple formulation that consists of a PN component for target capture and a coordination component for simultaneous arrival.The centralized algorithms come into effect when the global information of time-to-go estimation is obtained, whereas the decentralized algorithms have better performance when each missile can only collect information from neighbors.Numerical simulations demonstrate that the proposed coordination algorithms are feasible to perform the cooperative engagement of multiple missiles against both stationary and maneuvering targets.The effectiveness of the 3-D guidance laws is also discussed.