Texture compensation with multi-scale dilated residual blocks for image denoising

Neural Computing and Applications - Deep convolutional neural networks have achieved great success for image denoising recently. However, increasing the depth of the neural network cannot...     

颌骨重建中的图像分割和轮廓对应及分支问题

根据人体颌骨的形状特征,提出一系列有针对性的方法,在CT断层数据的基础上重建三维表面模型．研究的内容包括医学图像的分割和从轮廓线重建表面两个方面．首先,采用一种称为“非种子区域分割”方法提取物体的轮廓线;然后,建立一条反应颌骨走向的弓形“参照基准线”,充分利用轮廓线相对于它的“归一化位置”信息解决表面重建中的对应和分支问题;同时考虑相邻层的影响,使生成的表面更加光滑、自然．最后,提出“多阶凸包点对应匹配”的思想,用分层分段迭代的方法拼接三角面片．     

CAPSP——一个丝绸印花智能CAD/CAM系统

本文介绍了一个用于丝绸印花的智能CAD/CAM系统--CAPSP.CAPSP采用了基于 知识的处理技术,能非常有效地进行丝绸花样设计、人工画稿的分色处理以及输出满足丝绸印 花工艺的分色胶片.该系统已在国内若干丝绸印染厂成功地使用.     

环氧树脂改性方法研究进展

介绍了利用橡胶、有机硅、热致性液晶聚合物、互穿网络聚合物、核壳聚合物、纳米粒子、丙烯酸、腰果酚、微胶囊等改性环氧树脂的方法及其最新进展。     

一种基于向量运算的三维真实感纹理映射方法

为增强三维场景中纹理映射的真实感及映射效率，提出一种快捷且便于实现的基于向量运算的纹理映射方法。该方法实现方便，具有较高的处理速度。     

壁画图像分类中的分组多实例学习方法

针对壁画图像具有较大类内差异的特点,提出一种分组策略,将样本空间划分为不同的子空间,每一个子空间中的所有训练样本训练分类器模型,测试阶段,根据测试样本落到的子空间来选择不同的分类模型对测试样本进行分类。在各个子空间训练分类器时,为了克服壁画图像较强背景噪音的影响,我们将每一幅壁画图像样本看作多个实例的组成,采用多实例学习的方式来训练分类器。训练过程中,我们引入隐变量用于标识每一个实例,隐变量的存在使得分类器的优化问题不是一个凸问题,因此我们无法用梯度下降法去直接求解,本文中我们采用迭代的方式训练Latent SVM作为每一个子空间的分类器。实验证明了本文的分类模型能够较大程度的解决壁画图像的类内差异以及背景噪音对分类结果造成的影响。     

结合Gamma修正的色彩量化新算法

色彩量化的最终目的是使得视觉效果上的最化图像与原图像的差别（即失真）最小，量化的应用又对算法效率提出很高的要求，文中提出一种结合Gamma修正的量化算法，速度明显快于中位切分等以往算法，并且量化图像的质量近似于，甚至部分视觉效果优于这些算法，该算法是一种切实有效的图像量化方法，它在计算复杂度和量人结果的精确度上进行了折衷。     

Non‐Local Image Inpainting Using Low‐Rank Matrix Completion

In this paper, we propose a highly accurate inpainting algorithm which reconstructs an image from a fraction of its pixels. Our algorithm is inspired by the recent progress of non‐local image processing techniques following the idea of ‘grouping and collaborative filtering’. In our framework, we first match and group similar patches in the input image, and then convert the problem of estimating missing values for the stack of matched patches to the problem of low‐rank matrix completion, and finally obtain the result by synthesizing all the restored patches. In our algorithm, how to accurately perform patch matching process and solve the low‐rank matrix completion problem are key points. For the first problem, we propose a robust patch matching approach, and for the second task, the alternating direction method of multipliers is employed. Experiments show that our algorithm has superior advantages over existing inpainting techniques. Besides, our algorithm can be easily extended to handle practical applications including rendering acceleration, photo restoration and object removal.     

3D palmprint recognition using shape index representation and fragile bits

Recent years have witnessed a growing interesting in developing automatic palmprint recognition methods. Most of the previous works have concentrated on two dimensional (2D) palmprint recognition in the past decade. However, the shape information is lost in 2D plamprint images. What’s more, 2D plamprint recognition is not robust enough in practice since its data could be easily counterfeited or contaminated by noise. Consequently, three dimensional (3D) palmprint recognition is treated as an important alternative road to both enhance the performance and robustness of current available palmprint recognition systems. In this paper, we first explore geometrical information of 3D palmprint data by employing shape index formulation, from which Gabor wavelet features are then extracted. Furthermore, we first discover that by incorporating fragile bits information, the performance of coding strategy related 3D recognition method can be further improved. Experiments conducted on the public available 3D plamprint database validate that our method can obtain the highest recognition performance among the state-of-the-art methods estimated.     

轮廓整体结构约束的壁画图像相似性度量

图像分类是计算机视觉的重要研究领域,选择一种特征建立图像间的相似性度量是图像分类的关键问题.鉴于壁画图像自身的特点,轮廓特征是能够表达壁画图像语义的重要特征.研究表明轮廓可以作为图像的重要特征进行图像的识别和分类,但以往研究往往是通过两两最相似轮廓间的chamfer距离来计算图像间的相似性,或者对轮廓建立局部描述符,聚类生成词典,用统计直方图的方式描述图像特征,然后用支持向量机(SVM)进行图像分类.这些方法都忽略了轮廓间的整体结构关系,缺乏对所有轮廓的整体性描述,而现实中一幅图像的语义更多的是一种整体上的语义.基于轮廓整体结构的图像间相似性度量方法,图像间轮廓的相似度计算要受到与其他轮廓空间结构关系的约束,由此生成的相似度更能够表达两幅图像的整体相似程度.实验结果表明本文方法在壁画图像的分类上相对于没有整体结构约束的方法精度有所提高.