Merging radiometric grids using histogram matching

Large-scale compilations of airborne geophysical data are an important part of regional-scale mineral exploration and in most cases, the compilation involves merging datasets of varying quality, acquired over a long period of time. Merging radiometric datasets involves the additional complication that many older surveys were flown with uncalibrated spectrometer systems. Conventional grid merging is based on calculation of base-level shift and scaling factors for each grid with the grid edges feathered. However, even after these corrections, soil moisture differences between surveys acquired over a long period of time and at different seasons when soil moisture content varied introduce scaling errors into the estimated radioelement concentrations. An alternative method based on histogram matching is suggested as an improvement on existing methods. Source code in Matlab format is available from the server at www.iamg.org.     

Scale-invariant template matching using histogram of dominant gradients

This paper presents a histogram-based template matching method that copes with the large scale difference between target and template images. Most of the previous template matching methods are sensitive to the scale difference between target and template images because the features extracted from the images are changed according to the scale of the images. To overcome this limitation, we introduce the concept of dominant gradients and describe an image as the feature that is tolerant to scale changes. To this end, we first extract the dominant gradients of a template image and represent the template image as the grids of histograms of the dominant gradients. Then, the arbitrary regions of a target image with various locations and scales are matched with the template image via histogram matching. Experimental results show that the proposed method is more robust to scale difference than previous template matching techniques.     

Uniform texture synthesis and texture mapping using global parameterization

Texture mapping and texture synthesis are two popular methods for the decoration of surfaces with visual detail. Here, an existing challenge is to preserve, or at least balance, two competing metrics: scale and angle. In this paper we present two methods for this, both based on global conformal parameterization. First, we describe a texture synthesis algorithm for surfaces with arbitrary topology. By using the conformal parameterization, the 3D surface texture synthesis problem can be converted to a 2D image synthesis problem, which is more intuitive, easier, and conceptually simpler. While the conformality of the parameterization naturally preserves the angles of the texture, in this paper we provide a multi-scale technique to also maintain a more uniform area scaling factor. A second novel contribution is to employ the global parameterization to simultaneously preserve orthogonality and size in texture mapping. For this, we show that a conformal factor-driven mass-spring method offers a convenient way to trade off these two qualitative metrics. Our algorithms are simple, efficient and automatic, and they are theoretically sound and universal to general surfaces as well.     

Automated eye motion using texture synthesis

Modeling human eyes requires special care. The goal of this paper is to synthesize realistic eye-gaze and blink motion, accounting for any possible correlations between the two. The technique adopts a data-driven texture synthesis approach to the problem of synthesizing realistic eye motion. The basic assumption is that eye gaze probably has some connection with eyelid motion, as well as with head motion and speech. But the connection is not strictly deterministic and would be difficult to characterize explicitly. A major advantage of the data-driven approach is that the investigator does not need to determine whether these apparent correlations actually exist. If the correlations occur in the data, the synthesis (properly applied) will reproduce them.     

High efficiency and quality: large graphs matching

Graph matching plays an essential role in many real applications. In this paper, we study how to match two large graphs by maximizing the number of matched edges, which is known as maximum common subgraph matching and is NP-hard. To find exact matching, it cannot a graph with more than 30 nodes. To find an approximate matching, the quality can be very poor. We propose a novel two-step approach that can efficiently match two large graphs over thousands of nodes with high matching quality. In the first step, we propose an anchor-selection/expansion approach to compute a good initial matching. In the second step, we propose a new approach to refine the initial matching. We give the optimality of our refinement and discuss how to randomly refine the matching with different combinations. We further show how to extend our solution to handle labeled graphs. We conducted extensive testing using real and synthetic datasets and report our findings in this paper.     

螺旋线状搜索的快速块匹配纹理合成

为了避免纹理映射技术可能带来接缝走样的缺陷和过程纹理合成中复杂参数的调试,采用基于样图的纹理合成方法提出了一种新算法.该算法基于纹理的连贯性,在采用徐晓刚螺旋线状搜索算法的同时,结合了梁林的块拼贴纹理合成算法,即利用连贯性在样图中已合成纹理块位置向邻域扩展进行螺旋搜索,直到搜索到最佳匹配纹理块,然后进行纹理合成.大量实验结果表明,该算法与上述两种算法相比在合成效果上更加理想,合成时间也大大提高.     

Texture mixing and texture movie synthesis using statisticallearning

We present an algorithm based on statistical learning for synthesizing static and time-varying textures matching the appearance of an input texture. Our algorithm is general and automatic and it works well on various types of textures, including 1D sound textures, 2D texture images, and 3D texture movies. The same method is also used to generate 2D texture mixtures that simultaneously capture the appearance of a number of different input textures. In our approach, input textures are treated as sample signals generated by a stochastic process. We first construct a tree representing a hierarchical multiscale transform of the signal using wavelets. From this tree, new random trees are generated by learning and sampling the conditional probabilities of the paths in the original tree. Transformation of these random trees back into signals results in new random textures. In the case of 2D texture synthesis, our algorithm produces results that are generally as good as or better than those produced by previously described methods in this field. For texture mixtures, our results are better and more general than those produced by earlier methods. For texture movies, we present the first algorithm that is able to automatically generate movie clips of dynamic phenomena such as waterfalls, fire flames, a school of jellyfish, a crowd of people, etc. Our results indicate that the proposed technique is effective and robust     

Video texture modelling and synthesis using fractal processes

The authors propose a new approach for the synthesis of natural video textures using a fractal- based approach. Specifically, a video texture is modelled according to the three-dimensional (3D) extended self-similar (ESS) model introduced, which generalises the fractional Brownian motion process. The analysis of original video textures is based on the estimation of the autocorrelation functions (ACFs) of the textures' increments. The 3D-ESS model is then used to synthesise a process whose increments have the same ACFs of the given prototype. The synthesis is accomplished by generalising to the 3D case the incremental Fourier synthesis algorithm. Experimental results for the analysis and synthesis of natural video textures are eventually provided.     

Efficient texture synthesis using strict Wang Tiles

Wang Tiles are constructed from four texture samples, arranged so they can always match a choice of other tiles at two edges. Because they are precomputed, Wang Tiles are a very efficient way to generate textures on the fly. But matching problems occur within tiles and at the corners of adjacent tiles. By replacing the edge-matching texture samples with a new sample in the center of the tile, and using the graph cut path-finding algorithm, we overcome these problems and introduce additional texture diversity. Our s-Wang Tiles are a stricter interpretation of the original Wang Tile design, and our tile set is also smaller than that required by ω-Tiles: only eight different tiles are required for a non-repetitive titling.     

Facial image synthesis using skin texture recording

A significant issue in synthesizing realistic faces is the representation of skin grain and wrinkles. This paper describes a new approach based on the registered body of a real person. This recording allows simultaneously registering of the 3-D coordinates of a point and the corresponding reflected intensity. Using a 4-D B-spline surface to reconstruct the face, we come close to achieving a photographic result.     

Shapeme histogram projection and matching for partial object recognition

Histograms of shape signature or prototypical shapes, called shapemes, have been used effectively in previous work for 2D/3D shape matching and recognition. We extend the idea of shapeme histogram to recognize partially observed query objects from a database of complete model objects. We propose representing each model object as a collection of shapeme histograms and match the query histogram to this representation in two steps: 1) compute a constrained projection of the query histogram onto the subspace spanned by all the shapeme histograms of the model and 2) compute a match measure between the query histogram and the projection. The first step is formulated as a constrained optimization problem that is solved by a sampling algorithm. The second step is formulated under a Bayesian framework, where an implicit feature selection process is conducted to improve the discrimination capability of shapeme histograms. Results of matching partially viewed range objects with a 243 model database demonstrate better performance than the original shapeme histogram matching algorithm and other approaches.     

Real-time structured texture synthesis and editing using image-mesh analogies

We present a novel texture synthesis technique designed to reproduce at real-time frame-rates example texture images, with a special focus on patterns characterized by structural arrangements. Unlike current pixel-, patch- or texton-based schemes, that operate in image space, our approach is structural. We propose to assimilate texture images to corresponding 2D geometric meshes (called texture meshes). Our analysis mainly consists in generating automatically these meshes, while synthesis is then based on the creation of new vertex/polygon distributions matching some arrangement map. The output texture image is obtained by rasterizing the previously generated polygons using graphics hardware capabilities, which guarantees high speed performance. By operating in geometry space instead of image/pixel space, the proposed structural approach has a major advantage over current techniques: beyond pure texture reproduction, it allows us to define various tools, which allow users to further modify locally or globally and in real-time structural components of textures. By controlling the arrangement map, users can substitute new meshes in order to completely modify the structural appearance of input textures, yet maintaining a certain visual resemblance with the initial example image.     

基于局部累积直方图和纹理特征的图像检索方法

提出了结合HSI颜色空间的局部累积直方图和图像的纹理特征进行检索的新方法.在HSI颜色空间求局部累积直方图,既可以消除大量离散的零值点,又考虑到累积前后两种颜色的相似性,符合人眼的视觉感知特点;利用以灰度共生矩阵为基础的纹理特征对局部累积直方图检索的结果进行二次检索,充分考虑了图像的空间信息.避免单一的颜色特征描述图像的片面性.基于花卉图像库的检索实验结果表明,该方法可以取得良好的检索效果.     

Robust tile-based texture synthesis using artificial immune system

One significant problem in tile-based texture synthesis is the presence of conspicuous seams in the tiles. The reason is that sample patches employed as primary patterns of the tile set may not be well stitched if carelessly picked. In this paper, we introduce a robust approach that can stably generate an ω-tile set of high quality and pattern diversity. First, an extendable rule is introduced to increase the number of sample patches to vary the patterns in an ω-tile set. Second, in contrast to other concurrent techniques that randomly choose sample patches for tile construction, ours uses artificial immune system (AIS) to select the feasible patches from the input example. This operation ensures the quality of the whole tile set. Experimental results verify the high quality and efficiency of the proposed algorithm.     

Data-driven grasp synthesis using shape matching and task-based pruning

Human grasps, especially whole-hand grasps, are difficult to animate because of the high number of degrees of freedom of the hand and the need for the hand to conform naturally to the object surface. Captured human motion data provides us with a rich source of examples of natural grasps. However, for each new object, we are faced with the problem of selecting the best grasp from the database and adapting it to that object. This paper presents a data-driven approach to grasp synthesis. We begin with a database of captured human grasps. To identify candidate grasps for a new object, we introduce a novel shape matching algorithm that matches hand shape to object shape by identifying collections of features having similar relative placements and surface normals. This step returns many grasp candidates, which are clustered and pruned by choosing the grasp best suited for the intended task. For pruning undesirable grasps, we develop an anatomically-based grasp quality measure specific to the human hand. Examples of grasp synthesis are shown for a variety of objects not present in the original database. This algorithm should be useful both as an animator tool for posing the hand and for automatic grasp synthesis in virtual environments.     

GCP acquisition using simulated SAR and evaluation of GCP matching accuracy with texture features

Abstract

A method for ground control point (GCP) acquisition using a simulated synthetic aperture radar (SAR) image derived from a digital elevation model (DEM) is proposed. Also proposed is a method for the evaluation of the accuracy of GCP matching with texture features from a reference GCP chip image. Results from experiments with simulated GCP chip images as reference images and geometrically distorted GCP chip images, derived using simulated SAR images as current images, show good coincidence with GCP matching accuracy in terms of pixel distances between matched GCP points in reference and current chip images and texture features. In particular, the correlation coefficient between the angular second moment (ASM) and the matching accuracy is 0.757, followed by Ent (entropy), Horn (homoginiety), Dis (dissimilarity), Con (contrast), Var (variability coefficient) and Chi (Chi-square), for the skewed images while for the rotated images, Dis shows the highest correlation of 0.628, followed by Horn, Asm, Con, Ent, Chi and Var. Based on the proposed methods, one can easily generate GCP chips images from a DEM, and also evaluate GCP matching accuracy with texture features of simulated SAR from a GCP chip image.     

基于背景加权的联合颜色纹理直方图跟踪算法

针对在背景与目标颜色相近以及复杂场景中跟踪不准确的问题,提出一种改进的背景加权Mean Shift(均值漂移)跟踪算法,在目标颜色直方图中加入纹理特征,并将局部背景信息引入目标特征直方图中,以排除复杂背景的影响。实验证明,本文提出的算法在应对复杂背景及遮挡时比经典的Mean Shift算法以及背景加权Mean Shift算法更有效,且拥有不错的运行效率。     

基于纹理合成的水墨山水画自动绘制

通过分析中国山水画的一般创作技法,提出了基于纹理合成的水墨山水画绘制方法.将一幅图像作为控制图像,用于控制要绘制的区域轮廓和明暗色调;采集画家的手稿作为样本图像,通过纹理合成绘制出国画绘画中的各种皴、染笔触;在传统的纹理合成方法上,提出了一种目标控制的多级纹理合成算法,该算法能利用控制图像有效地控制纹理合成的结果.从而可以将一幅数字照片或简单的手绘图自动地转换成各种中国水墨画效果的图像.仿真结果证明了该方法对于各种山水画的绘制具有良好的效果.