The journal Communications in Numerical Methods in Engineering with Biomedical Applications becomes the International Journal for Numerical Methods in Biomedical Engineering (IJNMBE) from 1st January 2010

Communications in Numerical Methods in Engineering, founded by Roland W. Lewis in 1985, will change its title to the ‘International Journal for Numerical Methods in Biomedical Engineering’ and has a revised Aims and Scope. Copyright © 2009 John Wiley & Sons, Ltd.     

Mapping on the HEALPix grid

The natural spherical projection associated with the Hierarchical Equal-Area and Isolatitude Pixelization (HEALPix) is described and shown to be one of a hybrid class that combines the cylindrical equal-area and Collignon projections, not previously documented in the cartographic literature. Projection equations are derived for the class in general and are used to investigate its properties. It is shown that the HEALPix projection suggests a simple method of (i) storing and (ii) visualizing data sampled on the grid of the HEALPix pixelization, and also suggests an extension of the pixelization that is better suited for these purposes. Potentially useful properties of other members of the class are described, and new triangular and hexagonal pixelizations are constructed from them. Finally, the standard formalism is defined for representing the celestial coordinate system for any member of the class in the FITS data format.     

基于网格模板的最小欧式距离准则图像自动拼接技术

提出一种结合网格模板和最小欧式距离准则的图像自动拼接方法。方法选取图像重叠部分作为处理对象，运用边缘检测自动获取基准图像特征块，并提出基于网格模板的最小欧式距离准则用于计算匹配点，最后使用图像融合技术消除接缝。应用证明该方法拼接准确快速，实现简单，适合大部分图像拼接应用的需要。     

Design and elementary realization of the Vision Earth System

The Vision Earth System is a interactive system by employing B/S model. The system has the function of query display and mutuaUy displays relevant geologic information, integrating image information of one outcrop and realizing 3D geologic visualization. In this system, the basis is effective store, transmitting, display and quick query of enormous images and their properties data. From Java technology, this essay researches the elementary realization of Vision Earth System by adopting store formality of enormous images database,quick display image of website and quick image storage method.     

一种新的超声波心动图像分割算法

针对超声心动图像噪声大,边界模糊,灰度分布不均匀等特点,提出了一种新的图像分割算法.首先对超声图像进行滤波和边缘锐化等预处理,然后再使用GVFSnake模型对预处理后的图像进行分割,从而提取出心室的边界.经试验证明,这种新的超声心动图像分割算法,比传统的超声图像分割算法在图像分割精度上有显著的提高.     

基于小波变换和HIS变换的海冰SAR与光学遥感影像融合方法研究

Sea ice as a disaster has recently attracted a great deal of attention in China. Its monitoring has become a routine task for the maritime sector. Remote sensing, which depends mainly on SAR and optical sensors, has become the primary means for sea-ice research. Optical images contain abundant sea-ice multi-spectral information, whereas SAR images contain rich sea-ice texture information. If the characteristic advantages of SAR and optical images could be combined for sea-ice study, the ability of sea-ice monitoring would be improved. In this study, in accordance with the characteristics of sea-ice SAR and optical images, the transformation and fusion methods for these images were chosen. Also, a fusion method of optical and SAR images was proposed in order to improve sea-ice identification. Texture information can play an important role in sea-ice classification. Haar wavelet transformation was found to be suitable for the sea-ice SAR images, and the texture information of the sea-ice SAR image from Advanced Synthetic Aperture Radar(ASAR) loaded on ENVISAT was documented. The results of our studies showed that, the optical images in the hue-intensity-saturation(HIS) space could reflect the spectral characteristics of the sea-ice types more efficiently than in the red-green-blue(RGB) space, and the optical image from the China-Brazil Earth Resources Satellite(CBERS-02B) was transferred from the RGB space to the HIS space. The principal component analysis(PCA) method could potentially contain the maximum information of the sea-ice images by fusing the HIS and texture images. The fusion image was obtained by a PCA method, which included the advantages of both the sea-ice SAR image and the optical image. To validate the fusion method, three methods were used to evaluate the fused image, i.e., objective, subjective, and comprehensive evaluations. It was concluded that the fusion method proposed could improve the ability of image interpretation and sea-ice identification.     

基于主成分分析和决策级融合的高光谱图像分类方法研究

为了评价主成分分析方法和决策级数据融合方法对高光谱图像地物分类结果的影响,作者利用各分类器和主成分分量的优势,提出了两组地物分类结果的决策级融合策略,利用8种常用监督分类方法对高光谱原始图像和PCA变换后不同分量组合图分类得到的结果进行决策级融合,并应用覆盖黄河入海口新老河道交界处的CHRIS/PROBA高光谱图像开展实验研究。结果表明:直接采用每类地物分类精度最高的、空穴和缝隙采用总体分类精度最高的融合策略,在综合考虑生产者精度和用户精度的情形下,仅使用最大似然法、支持向量机和人工神经网络3种分类方法,按照分类精度从高到低的顺序进行的融合分类效果最好,总体分类精度为87.82%。与8种监督分类方法中效果最好的最大似然法相比,精度提高了2.7个百分点,同时明显减少了错分现象,尤其是对于分布面积较小的翅碱蓬和柽柳,滩涂被误分为翅碱蓬、芦苇被误分为柽柳的现象大大降低。     

基于声纳图像纹理特征的海底底质分类方法研究

一般不同底质的海底声纳图的纹理特征不同。重点分析了不同底质声纳图像纹理特征的差异,为底质分类的实现提供了基础。并提取了海底声纳图像的灰度共生矩阵,将灰度共生矩阵的统计特征作为特征向量。最后应用自组织迭代(ISODATA)分类算法依据对特征向量进行分类,从而实现了海底底质的划分。     

深度学习PaddlePaddle框架支持下的遥感智能视觉平台研究与实现

百度深度学习PaddlePaddle框架支持下的遥感智能视觉平台,能够运用深度学习技术实现遥感影像的智能建模、训练和解译。本文通过深入分析PaddlePaddle图像分割模型库PaddleSeg的图像处理深度学习算法模型DeepLabV3+、U²-Net及RetinaNet,开发设计了遥感智能视觉平台,实现了遥感影像的地块分割、变化检测和斜框检测等专业功能。研究表明：遥感智能视觉平台提取的图斑总面积是目视解译的80%、有效图斑比例为76%、错误图斑比例为18%,实现了快速有效的遥感图像智能处理。     

运用ULBP的高分辨率遥感影像感知哈希完整性认证算法

针对现有高分辨率遥感影像感知哈希认证算法中特征提取精度和算法稳健性不能兼顾的问题,本文提出一种运用ULBP的高分辨率遥感影像感知哈希完整性的认证算法。首先对遥感影像进行格网划分,将影像划分为多个子块,运用ULBP算法提取子块的纹理特征;然后计算每个子块内纹理特征的直方图分布,将其结果与均值二值化后得到子块的感知哈希序列;最后串联所有子块的感知哈希序列生成整幅影像的感知哈希值。在影像认证时,首先计算原始影像与待检测影像的哈希序列,然后计算两者的感知哈希序列平均汉明距离,完成对高分辨率遥感影像内容的完整性认证与篡改定位。试验表明,该算法能够识别高分辨率遥感影像中地物较为平滑的区域,同时对JPEG压缩、高斯噪声添加、BMP格式转换等操作具有良好的稳健性,为高分辨遥感影像完整性认证提供支持。