基于Curvelet变换和支持向量机的磁瓦表面缺陷识别方法

针对磁瓦表面缺陷对比度低、自动识别困难的问题,作者提出了一种对磁瓦图像应用快速离散Curvelet变换(FDCT)提取特征,并用支持向量机(SVM)分类器进行分类的磁瓦微小缺陷自动识别方法。该方法首先对磁瓦图像做分块处理,并对各分块图像应用FDCT,计算分解系数的l2范数,获得磁瓦不同方向的纹理频域特征;然后以归一化的分解系数l2范数作为支持向量机分类器的特征向量,对图像做出分类。对不同缺陷占比的图像进行实验测试,结果显示,当缺陷部分占分块图像的比例在1/64以上时正确识别率大于83%。     

基于NSCT和遗传算法的SAR图像和多光谱图像融合

合成孔径雷达(SAR)图像与多光谱图像成像机理和光谱特性差异较大,一般的融合方法很难取得满意的融合结果。文章提出了一种基于Nonsuosampled Contourlet transform(NSCT)和遗传算法的融合算法,首先将经过预处理后的图像进行NSCT分解,低频系数采取区域信息熵最大的准则融合;高频子带计算区域相关性,对相关性在不同阈值范围内的系数进行融合,阈值的选取采用遗传算法进行搜索;最后对融合系数进行NSCT逆变换,得到融合结果。仿真结果表明该算法显著优于基于像素点和基于区域的融合方法。     

柴达木盆地英西地区S3-1井渐新统下干柴沟组储集空间类型

近年来,柴达木盆地英西地区渐新统下干柴沟组的油气勘探取得了重大发现,但其主要储集空间类型一直是争论的焦点。基于对S3-1井的岩芯观察和系统的微观岩石学、结构学特征研究,总结出其主要储集空间类型为白云石晶间孔,而非溶蚀孔。其主要证据包括:①高沉积速率的暗色层段难以发生暴露溶蚀;②白云石为岩石最重要的矿物组分之一;③场发射扫描电镜下可见棱角状晶间孔广泛发育;④岩芯上观察到的孔洞系统在偏光显微镜下可见其均发育于裂缝之中,为盐类矿物结晶所致,非溶蚀而成;⑤“特低孔-特低渗”的物性特征;⑥较高的排驱压力、较小的连通孔喉半径以及极低的退汞效率;⑦荧光显微镜下表现为整体发光特征。这些发育极广的基质孔隙储油是英西地区亿吨级油田高产稳产的主控因素之一,研究结果对下一步勘探部署具有重要的指导意义。     

水蒸气对石灰石/白云石循环吸收CO_2能力影响

利用自制能实现等温下热重测量的实验系统,研究了水蒸气对不同粒径范围(75~97μm,150~250μm,355~450μm)石灰石与白云石在循环煅烧/碳酸化过程中对CO2吸收能力的影响。结果表明,当不考虑水蒸气时,白云石对CO2的吸收能力要高于石灰石;而考虑水蒸气时,两者对CO2的吸收能力则相差不多。碳酸化阶段水蒸气的存在提高了钙基吸收剂对CO2的吸收能力,尤其对石灰石作用更加明显。如在20%水蒸气下,石灰石循环第8次对CO2的吸收能力为0.24 g/g,而无水蒸气时仅为0.18 g/g。实验结果表明:比较石灰石与白云石对CO2的循环吸收能力时,水蒸气是重要的影响因素。     

一种特别的首饰铸造工艺——墨鱼骨铸造

墨鱼骨铸造因其独有的特色和肌理,被首饰艺术家用来创作个性化艺术首饰。本文结合实际操作介绍这种首饰铸造的工艺过程及技术要点。     

Morphological hat-transform scale spaces and their use in pattern classification

In this paper we present a multi-scale method based on mathematical morphology which can successfully be used in pattern classification tasks. A connected operator similar to the morphological hat-transform is defined, and two scale-space representations are built. The most important features are extracted from the scale spaces by unsupervised cluster analysis, and the resulting pattern vectors provide the input of a decision tree classifier. We report classification results obtained using contour features, texture features, and a combination of these. The method has been tested on two large sets, a database of diatom images and a set of images from the Brodatz texture database. For the diatom images, the method is applied twice, once on the curvature of the outline (contour), and once on the grey-scale image itself.     

Texture synthesis via the matching compatibility between patches

A new patch-based texture synthesis method is presented in this paper. By the method, a set of patches that can be matched with a sampled patch for growing textures effectively, called the matching compatibility between patches, is generated first for each patch, and the set is further optimized by culling the patches that may cause synthesis conflicts. In this way, similarity measurement calculation for selecting suitable patches in texture synthesis can be greatly saved, and synthesis conflicts between neighbouring patches are substantially reduced. Furthermore, retrace computation is integrated in the synthesis process to improve the texture quality. As a result, the new method can produce high quality textures as texture optimization, the best method to date for producing good textures, and run in a time complexity linear to the size of the output texture. Experimental results show that the new method can interactively generate a large texture in 1024 × 1024 pixels, which is very difficult to achieve by existing methods. Supported by the National Basic Research Program of China (Grant No. 2009CB320802), the National Natural Science Foundation of China (Grant Nos. 60773026, 60833007), the National High-Tech Research & Development Program of China (Grant Nos. 2006AA01Z306, 2008AA01Z301), and the Research Grant of University of Macau     

Rational Filters for Passive Depth from Defocus

A fundamental problem in depth from defocus is the measurement of relative defocus between images. The performance of previously proposed focus operators are inevitably sensitive to the frequency spectra of local scene textures. As a result, focus operators such as the Laplacian of Gaussian result in poor depth estimates. An alternative is to use large filter banks that densely sample the frequency space. Though this approach can result in better depth accuracy, it sacrifices the computational efficiency that depth from defocus offers over stereo and structure from motion. We propose a class of broadband operators that, when used together, provide invariance to scene texture and produce accurate and dense depth maps. Since the operators are broadband, a small number of them are sufficient for depth estimation of scenes with complex textural properties. In addition, a depth confidence measure is derived that can be computed from the outputs of the operators. This confidence measure permits further refinement of computed depth maps. Experiments are conducted on both synthetic and real scenes to evaluate the performance of the proposed operators. The depth detection gain error is less than 1%, irrespective of texture frequency. Depth accuracy is found to be 0.51.2% of the distance of the object from the imaging optics.     

Mean-field phase transitions and correlation functions for Gibbs random fields

The use of Gibbs random fields (GRF) to model images poses the important problem of the dependence of the patterns sampled from the Gibbs distribution on its parameters. Sudden changes in these patterns as the parameters are varied are known asphase transitions. In this paper we concentrate on developing a general deterministic theory for the study of phase transitions when a single parameter, namely, the temperature, is varied. This deterministic framework is based on a technique known as themean-field approximation, which is widely used in statistical physics. Our mean-field theory is general in that it is valid for any number of gray levels, any pairwise interaction potential, any neighborhood structure or size, and any set of constraints imposed on the desired images. The mean-field approximation is used to compute closed-form estimates of the critical temperatures at which phase transitions occur for two texture models widely used in the image modeling literature: the Potts model and the autobinomial model. The mean-field model allows us to gain insight into the Gibbs model behavior in the neighborhood of these temperatures. These analytical results are verified by computer simulations that use a novel mean-field descent algorithm. An important spinoff of our mean-field theory is that it allows us to compute approximations for the correlation functions of GRF models, thus bridging the gap between neighborhood-based and correlation-baseda priori image models.The work of I.M. Elfadel was supported in part by the National Science Foundation under grant MIP-91-17724. The work of A.L. Yuille was supported by the Brown, Harvard, and MIT Center for Intelligent Control Systems under U.S. Army Research Office grant DAAL03-86-C-0171, by the Defense Advanced Research Projects Agency under contract AFOSR-89-0506, and by the National Science Foundation under grant IRI-9003306.