Spectral calibration of digital cameras based on the spectral data of commercially available calibration charts is an ill-conditioned problem that has an infinite number of solutions. We introduce a method to estimate the sensor's spectral sensitivity function based on metamers. For a given patch on the calibration chart we construct numerical metamers by computing convex linear combinations of spectra from calibration chips with lower and higher sensor response values. The difference between the measured reflectance spectrum and the numerical metamer lies in the null space of the sensor. For each measured spectrum we use this procedure to compute a collection of color signals that lie in the null space of the sensor. For a collection of such spaces we compute the robust principal components, and we obtain an estimate of the sensor by computing the common null space spanned by these vectors. Our approach has a number of advantages over standard techniques: It is robust to outliers and is not dominated by larger response values, and it offers the ability to evaluate the goodness of the solution where it is possible to show that the solution is optimal, given the data, if the calculated range is one dimensional. © 2006 Optical Society of America.

Spectral calibration of digital cameras based on the spectral data of commercially available calibration charts is an illconditioned problem which has an infinite number of solutions. To improve upon the estimate, different constraints are commonly employed. Traditionally such constraints include: nonnegativity, smoothness, uni-modality and that the estimated sensors results in as good as possible response fit. In this paper, we introduce a novel method to solve a general ill-conditioned linear system with special focus on the solution of spectral calibration. We introduce a new approach based on metamerism. We observe that the difference between two metamers (spectra that integrate to the same sensor response) is in the null-space of the sensor. These metamers are used to robustly estimate the sensor-s null-space. Based on this nullspace, we derive projection operators to solve for the range of the unknown sensor. Our new approach has a number of advantages over standard techniques: It involves no minimization which means that the solution is robust to outliers and is not dominated by larger response values. It also offers the ability to evaluate the goodness of the solution where it is possible to show that the solution is optimal, given the data, if the calculated range is one dimensional. When comparing the new algorithm with the truncated singular value decomposition and Tikhonov regularization we found that the new method performs slightly better for the training set with noticeable improvements for the test data. 

Level set methods are a popular way to solve the image segmentation problem in computer image analysis. A contour is implicitly represented by the zero level of a signed distance function, and evolved according to a motion equation in order to minimize a cost function. This function defines the objective of the segmentation problem and also includes regularization constraints. Gradient descent search is the de facto method used to solve this optimization problem. Basic gradient descent methods, however, are sensitive for local optima and often display slow convergence. Traditionally, the cost functions have been modified to avoid these problems. In this work, we instead propose using a modified gradient descent search based on resilient propagation (Rprop), a method commonly used in the machine learning community. Our results show faster convergence and less sensitivity to local optima, compared to traditional gradient descent.

This paper presents a technique for creating a smooth, closed surface from a set of 2D contours, which have been extracted from a 3D scan. The technique interprets the pixels that make up the contours as points in R3 and employs multi-level partition of unity (MPU) implicit models to create a surface that approximately fits to the 3D points. Since MPU implicit models additionally require surface normal information at each point, an algorithm that estimates normals from the contour data is also described. Contour data frequently contains noise from the scanning and delineation process. MPU implicit models provide a superior approach to the problem of contour-based surface reconstruction, especially in the presence of noise, because they are based on adaptive implicit functions that locally approximate the points within a controllable error bound. We demonstrate the effectiveness of our technique with a number of example datasets, providing images and error statistics generated from our results. © 2006 Elsevier Inc. All rights reserved.

Handbook of Biomedical Image Analysis: Registration Models (Volume III) is dedicated to the algorithms for registration of medical images and volumes. This volume is aimed at researchers and educators in imaging sciences, radiological imaging, clinical and diagnostic imaging, biomedical engineering, physicists covering different medical imaging modalities and researchers in applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry.

Imagine an ant walking around on the curved surface of a plant, a radio amateur planning to broadcast to a distant location across the globe or a pilot taking o from an airport - all of them are helped by egocentric maps of the world around them that shows directions and distances to various remote places. It is not surprising that this idea has already been used in cartography, where it is known as Azimuthal Equidistant Projection (AEP). If Earth is approximated by a sphere, distances and directions between two places are computed from arcs along great circles. In physics and mathematics, the same idea is known as Riemannian Normal Coordinates (RNC). It has been given a precise and general denition for surfaces (2-D), curved spaces (3-D) and generalized to smooth manifolds (N-D). RNC are the Cartesian coordinates of vectors that index points on the surface (or manifold) through the so called exponential map, which is a well known concept in dierential geometry. They are easily computed for a particular point if the inverse of the exponential map, the logarithm map, is known. Recently, RNC and similar coordinate systems have been used in computer graphics, visualization and related areas of research. In Fig. 1 for instance, RNC are used to produce a texture on the Stanford bunny through decal compositing. Given the growing use of RNC, which is further elaborated on in the next section, it is meaningful to develop accurate and reproducible techniques to compute this parameterization. In this paper, we describe a technique to compute RNC for surfaces represented by triangular meshes, which is the predominant representation of surfaces in computer graphics. The method that we propose has similarities to the Logmap framework, which has previously been developed for dimension reduction of unorganized point clouds in high-dimensional spaces, a.k.a. manifold learning. For this reason we sometimes refer to it as "Logmap for triangular meshes" or simply Logmap.

A print production workflow consists of a number of systems

specialized at executing specific tasks. In order to realize an

efficient workflow it is not enough to simply assemble all the

required systems, the systems must also communicate with each

other and exchange information. The printing industry has used

several approaches for integrating systems. A common

approach has been to use so-called “hot folders” to exchange

content files, such as PDF documents, between systems.

Another approach, which focuses on the exchange of production

and configuration data, is the XML-based Job Definition

Format (JDF) and its messaging protocol Job Messaging

Format (JMF).

The need to integrate heterogeneous systems is nothing unique

to the printing industry. The experience and knowledge in this

area has been documented in several pattern languages. By

applying a combination of several such pattern languages, this

paper presents a hypothetical integration architecture that

enables a system to communicate with other systems using JMF

messaging.

The print production workflow consists of various disparate systems — from production equipment to management information systems. During the production of a printed product, information regarding the product must be communicated between the systems in the workflow. Job Definition Format (JDF) is an industry standard that specifies this information interchange. It specifies a digital job ticket format for exchanging administrative and technical information related to a print job, and a messaging protocol for communicating information between the systems in the workflow. This licentiate thesis explores different aspects of integrating systems in a JDF-enabled print production workflow.

Paper III and Paper IV analyze the properties of JDF’s messaging protocol—Job Messaging Format (JMF)—and discuss design solutions for a JMF integration layer.

Paper I presents a software tool for simulating systems in the print production workflow. The tool is based on an open source software library, called the Elk Framework, which has been developed within the framework of these licentiate studies. The Elk Framework provides the base services required by a piece of JDF-enabled production equipment, called a Device/Worker in JDF parlance.

Paper II presents a software tool that was developed for testing the simulation tool presented in Paper I. The test tool, named Alces, can be used for testing if JDF-enabled systems conform to the JDF Specification.

We have previously shown that it is possible to construct a coordinate system in the space of illumination spectra such that the coordinate vectors of the illuminants are located in a cone. Changes in the space of illuminants can then be described by an intensity related scaling and a transformation in the Lorentz group SU(1,1). In practice it is often difficult and expensive to measure these coordinate vectors. Therefore it is of interest to estimate the characteristics of an illuminant from an RGB image captured by a camera. In this paper we will investigate the relation between sequences of illuminants and statistics computed from RGB images of scenes illuminated by these illuminants. As a typical example we will study sequences of black body radiators of varying temperature. We have shown earlier that black body radiators in the mired parametrization can be described by one-parameter groups of the Lorentz group SU(1,1). In this paper we will show that this group theoretical structure of the illuminant space induces a similar structure in spaces of statistical descriptors of the resulting RGB images. We show this relation for mean vectors of RGB images, for RGB histograms and for histograms of images obtained by applying certain spatiospectral linear filters to the RGB images. As a result we obtain estimates of the color temperature of the illuminant from sequences of RGB images of scenes under these illuminants.

We consider several collections of multispectral color signals and describe how linear and non-linear methods can be used to investigate their internal structure. We use databases consisting of blackbody radiators, approximated and measured daylight spectra, multispectral images of indoor and outdoor scenes under different illumination conditions and numerically computed color signals. We apply Principal Components Analysis, group-theoretical methods and three manifold learning methods: Laplacian Eigenmaps, ISOMAP and Conformal Component Analysis. Identification of low-dimensional structures in these databases is important for analysis, model building and compression and we compare the results obtained by applying the algorithms to the different databases.

In this paper, we use Riemann geometry to develop a generalframework for the characterization of and mapping betweencolor spaces. Within this framework we show how to constructmaps, so-called isometries, between two color spaces that preservecolor differences. We illustrate applications of this frameworkby constructing a uniform color space and developing algorithmsfor color reproduction on different printers and correctionof color-vision for color-weak observers.

Through a study of the van der Waals interaction between a solid and an air-water interface, we investigate the practical and fundamental problem of the limiting height at which an object can approach a free surface. A numerical study of the interface shape reveals dependencies governed by two disparate length scales associated with the relative strengths of the van der Waals and bouyancy forces, to surface tension. A study of the limits of solvability of the governing equation has led to the principal result: a closed-form expression for the absolute limiting height to which an object can be lowered to the air-water interface. The formula depends explicitly and only on the Hamaker constant of the van der Waals force and the geometry of the solid.

The shape of the air-water interface deformed by a van der Waals stress induced by a paraboloid shaped solid body is addressed and discussed. Emphasis is placed on the existence limit of solutions to the governing Euler-Lagrange equation for the equilibrium shape. Two legitimate solutions, one stable and one unstable, are found to converge at the existence limit, giving a numerical criterion for establishing critical physical conditions guaranteeing absolute stability. Insight is aided by a study of an analogous mechanical problem that exhibits very similar properties. Among numerical data produced are critical lower height limits of the paraboloid to the air-water surface and associated peak deformation heights and their dependencies on physical parameters. Of further interest to experimentalists in the surface force field are the variations in peak deformation height and total surface force on the solid as a function of position of the paraboloid, paraboloid geometry, and strength of the van der Waals stress.

In this paper the problem of the synthesis of plucked strings by means of physically inspired models is reconsidered in the context of the player-s interaction with the virtual instrument. While solutions for the synthesis of guitar tones have been proposed, which are excellent from the acoustic point of view, the problem of the control of the physical parameters directly by the player has not received sufficient attention. In this paper we revive a simple model previously presented by Cuzzucoli and Lombardo for the player-s touch. We show that the model is affected by an inconsistency that can be removed by introducing the finger/pick perturbation in a balanced form on the digital waveguide. The results, together with a more comprehensive model of the guitar have been implemented in a VST plugin, which is the starting point for further research.

Fractal modulation is obtained by forming a power weighted superposition of scaled and modulated versions of the signal. The resulting signal is self-similar with fractal characteristics. In this paper we explore fractal modulation as a powerful method to generate rich signals, useful both for the synthesis of complex sounds, like the sounds from natural events or ecological sounds, or as control functions of audio effects. The wavelet transform can be used as an efficient tool in order to generate a subset of fractal modulated signals that are power homogeneous. Any signal used as a seed for fractal modulation is transformed into a multiscale sound by means of a tree-structured multirate filter bank. Moreover, by superimposing a structured modulation scheme one can generate pseudo-periodic sounds whose partials have fractal behavior.

Frequency warping is a desirable building block for sound effects and synthesis. Physical model driven pitch shifting of inharmonic sounds and the transformation of harmonic into inharmonic sounds are the main features of frequency warping effects. However, frequency warping sound signals is a non-causal and computationally expensive operation. In recent work [1] we showed that multirate filter bank s derived from a modified phase vocoder structure are suitable for the real-time approximate computation of frequency warping. The approximation is proven to be very accurate from both numerical and perceptual points of view. In this paper we extend the principles of the original design to implement time-varying frequency warping methods. The proposed algorithm is suitable for inclusion in the synthesis of systems with dynamic stiffness and for the production of captivating audio effects.

Frequency warping is a modifier that acts on sound signals by remapping the frequency axis. Thus, the spectral content of the original sound is displaced to other frequencies. At the same time, the phase relationship among the signal components is altered, nonlinearly with respect to frequency. While this effect is interesting and has several applications, including in the synthesis by physical models, its use has been so far limited by the lack of an accurate and flexible real-time algorithm. In this paper we present methods for frequency warping that are based on local approximations of the warping operators and allow for real-time implementation. Filter bank structures are derived that allow for efficient realization of the approximate technique. An analysis of the error is also presented, which shows that both numerical and perceptual errors are within acceptable limits. Furthermore, the approximate implementation allows for a larger variety of warping maps than that achieved by the classical (non-causal) first-order allpass cascade implementation.

In this paper, we provide a model of the plectrum, or guitar pick, for use in physically inspired sound synthesis. The model draws from the mechanics of beams. The profile of the plectrum is computed in real time based on its interaction with the string, which depends on the movement impressed by the player and the equilibrium of dynamical forces. A condition for the release of the string is derived, which allows to drive the digital waveguide simulating the string to the proper state at release time. The acoustic results are excellent, as verified in the sound examples provided.

A digital gray scale image generally consists of 256 different gray tones. Printers and image setters normally generate much fewer levels and mostly only two levels. Therefore, in order to be able to display a digital cone-tone image by a multilevel device it has to be transformed into an image with fewer levels. The technique doing this transformation is called multi-level halftoning, and in the case of bilevel devices it is simply called halftoning. In this paper we propose a novel (bilevel) halftoning technique that is based on multilevel halftoning. The proposed method can also be categorized as belonging to hybrid amplitude modulated (AM)/ frequency modulated (FM) techniques. In this method the original digital image is firstly halftoned by a multilevel FM halftoning. Each level in the multilevel halftoned image is then replaced by a halftone table (microcell). An approach for extending any bilevel FM halftoning method to a multilevel method is also presented in this paper. The performance of the proposed method is examined by a number of illustrations where nonmodified error diffusion and our FM method are used. The problem with maze-like artifacts that occur when our FM halftoning, or similar methods such as DBS, are used as the macroscreen is discussed and a simple solution is introduced. An approach for extending the proposed method to be used in situations where the halftone dots cannot be produced smaller than a specific size is also proposed and examined. This modified version of the method can be useful for flexography, where the dots normally cannot be produced smaller than a critical size.

When a color image is halftoned its color channels are normally halftoned independently. The dots in different channels are placed independent of each other and consequently the final result may not be of high quality even if a. well performing monochromatic halftoning method has been used. In this article we propose a method that halftones the channels of the color image in a context dependent manner. Since the yellow ink on a white paper is hardly visible, only cyan and magenta separations need to be halftoned dependently. We also show that dependent color halftoning not only increases the halftone image quality but also decreases the amount of ink needed to reproduce different colors.

Most printing devices, such as laser and ink jet printers and many print presses, are restricted to very few colors. The contone images should therefore be transformed into binary ones before being printed. The techniques doing this transformation are referred to as halftoning methods. Halftoning methods can be divided into two main categories, namely AM (Amplitude Modulated) and FM (Frequency Modulated). Some printing methods, such as Flexography, are not able to produce dots sufficiently small in order to handle the highlights and the shadows of the original image by using just an AM halftoning method. In this article we propose a hybrid halftoning method that incorporates AM and FM technologies in order to overcome this problem. The strategy is to use an FM method in the highlights (and the shadows) of the image and an AM method in the rest of the image.

Printed dots appear bigger than their reference size in the original bitmap. This is because of the physical and optical dot gain. In order to overcome the problem original images are compensated for dot gain. The compensation is usually done by using a dot gain curve for each colour separation. In this paper we firstly show that using only one dot gain curve works well for black, but not for any of the other three colours, i.e. cyan, magenta or yellow. We also present a new approach to calculate colour values where three different curves are used for each colour separation. In order to evaluate the proposed approach we compare the results of our method with the results when only one dot gain curve is used for each colour, both for Murray-Davies and Yule-Nielsen models. In the case of only one dot gain curve for each separation we use the curve that gives a minimized ∆ELab using least squares method. The experiments and calculations show that our approach gives a better approximation of the resulting colour coordinates.

The problem of estimating spectral reflectances from the responses of a digital camera has received considerable attention recently This problem can be cast as a regularized regression problem or as a statistical inversion problem. We discuss some previously suggested estimation methods based on critically undersampled RGB measurements and describe some relations between them. We concentrate mainly on those models that are using a priori information in the form of high-resolution measurements. We use the "kernel machine" framework in our evaluations and concentrate on the use of multiple illuminations and on the investigation of the performance of global and locally adapted estimation methods. We also introduce a nonlinear transformation of reflectance values to ensure that the estimated reflection spectra fulfill physically motivated boundary conditions. The reported experimental results are derived from measured and simulated camera responses from the Mansell Matte, NCS, and Pantone data sets.

Using ordinary digital cameras as relatively cheap measurementdevices for estimating spectral color properties has becomean interesting alternative to making pointwise high precisionspectral measurements with special equipments like photospectrometers.The results obtained with these methods cannotcompete with the quality of the traditional high resolutiondevices but they are very attractive since the equipment is relativelycheap and instant measurements are obtained for millionsof measurement points.In this paper we investigate the problem of estimating reflectancespectra from measurements taken with ordinary digitalRGB cameras. We study the effects of using multiple illuminationsand treat the estimation of the reflectance spectra asa regression or a statistical inversion problem. We use both,linear- and non-linear estimation methods where we focus onusing reproducing kernels to avoid explicit formulation of nonlinearities.We also include non-linear conditions based on theproperties of the reflection spectra. Munsell Matte color andPantone are used as data sets to support the proposed methods.The experiments show that the proposed methods improve the estimationresults when compared to standard linear methods.

This article introduces the Hierarchical Run-Length Encoded (H-RLE) Level Set data structure. This novel data structure combines the best features of the DT-Grid ( of Nielsen and Museth [ 2004]) and the RLE Sparse Level Set ( of Houston et al. [ 2004]) to provide both optimal efficiency and extreme versatility. In brief, the H- RLE level set employs an RLE in a dimensionally recursive fashion. The RLE scheme allows the compact storage of sequential nonnarrowband regions while the dimensionally recursive encoding along each axis efficiently compacts nonnarrowband planes and volumes. Consequently, this new structure can store and process level sets with effective voxel resolutions exceeding 5000 x 3000 x 3000 ( 45 billion voxels) on commodity PCs with only 1 GB of memory. This article, besides introducing the H- RLE level set data structure and its efficient core algorithms, also describes numerous applications that have benefited from our use of this structure: our unified implicit object representation, efficient and robust mesh to level set conversion, rapid ray tracing, level set metamorphosis, collision detection, and fully sparse fluid simulation ( including RLE vector and matrix representations.) Our comparisons of the popular octree level set and Peng level set structures to the H- RLE level set indicate that the latter is superior in both narrowband sequential access speed and overall memory usage.

We present work in progress on concurrent ray tracing with distributed computers using ``off-the-shelf'' open source software. While there exists numerous open source ray tracers, very few offer support for state-of-the-art concurrent computing. However, it is a well known fact that ray tracing is computationally intensive and yet prevails as the preferred algorithm for photorealistic rendering. Thus, the current work is driven by a desire for a simple programming strategy (or recipe) that allows pre-existing ray tracing code to be parallelized on a heterogenous cluster of available office computers - strictly using open source components. Simplicity, stability, efficiency and modularity are the driving forces for this engineering project, and as such we do not claim any novel research contributions. However, we stress that this project grew out of a real-world need for a render cluster in our research group, and consequently our solutions have a significant practical value. In fact some of our results show a close to optimal speedup when considering the relative performances of each node. In this systems paper we aim at sharing these solutions and experiences with other members of the graphics community.

One of the most common visualization tasks is the extraction of significant boundaries, often performed with iso- surfaces or level set segmentation. Isosurface extraction is simple and can be guided by geometric and topological analysis, yet frequently does not extract the desired boundary. Level set segmentation is better at boundary extrac- tion, but either leads to global segmentation without edges, [CV01], that scales unfavorably in 3D or requires an initial estimate of the boundary from which to locally solve segmentation with edges. We propose a hybrid system in which topological analysis is used for semi-automatic initialization of a level set segmentation, and geometric information bounded topologically is used to guide and accelerate an iterative segmentation algorithm that com- bines several state-of-the-art level set terms. We thus combine and improve both the flexible isosurface interface and level set segmentation without edges.