Space-dependent color gamut mapping: a variational approach.

Gamut mapping deals with the need to adjust a color image to fit into the constrained color gamut of a given rendering medium. A typical use for this tool is the reproduction of a color image prior to its printing, such that it exploits best the given printer/medium color gamut, namely the colors the printer can produce on the given medium. Most of the classical gamut mapping methods involve a pixel-by-pixel mapping and ignore the spatial color configuration. Recently proposed spatial-dependent approaches for gamut mapping are either based on heuristic assumptions or involve a high computational cost. In this paper, we present a new variational approach for space-dependent gamut mapping. Our treatment starts with the presentation of a new measure for the problem, closely related to a recent measure proposed for Retinex. We also link our method to recent measures that attempt to couple spectral and spatial perceptual measures. It is shown that the gamut mapping problem leads to a quadratic programming formulation, guaranteed to have a unique solution if the gamut of the target device is convex. An efficient numerical solution is proposed with promising results.     

Multiplicative Operator Splittings in Nonlinear Diffusion: From Spatial Splitting to Multiple Timesteps

Operator splitting is a powerful concept used in many diversed fields of applied mathematics for the design of effective numerical schemes. Following the success of the additive operator splitting (AOS) in performing an efficient nonlinear diffusion filtering on digital images, we analyze the possibility of using multiplicative operator splittings to process images from different perspectives.We start by examining the potential of using fractional step methods to design a multiplicative operator splitting as an alternative to AOS schemes. By means of a Strang splitting, we attempt to use numerical schemes that are known to be more accurate in linear diffusion processes and apply them on images. Initially we implement the Crank-Nicolson and DuFort-Frankel schemes to diffuse noisy signals in one dimension and devise a simple extrapolation that enables the Crank-Nicolson to be used with high accuracy on these signals. We then combine the Crank-Nicolson in 1D with various multiplicative operator splittings to process images. Based on these ideas we obtain some interesting results. However, from the practical standpoint, due to the computational expenses associated with these schemes and the questionable benefits in applying them to perform nonlinear diffusion filtering when using long timesteps, we conclude that AOS schemes are simple and efficient compared to these alternatives.We then examine the potential utility of using multiple timestep methods combined with AOS schemes, as means to expedite the diffusion process. These methods were developed for molecular dynamics applications and are used efficiently in biomolecular simulations. The idea is to split the forces exerted on atoms into different classes according to their behavior in time, and assign longer timesteps to nonlocal, slowly-varying forces such as the Coulomb and van der Waals interactions, whereas the local forces like bond and angle are treated with smaller timesteps. Multiple timestep integrators can be derived from the Trotter factorization, a decomposition that bears a strong resemblance to a Strang splitting. Both formulations decompose the time propagator into trilateral products to construct multiplicative operator splittings which are second order in time, with the possibility of extending the factorization to higher order expansions. While a Strang splitting is a decomposition across spatial dimensions, where each dimension is subsequently treated with a fractional step, the multiple timestep method is a decomposition across scales. Thus, multiple timestep methods are a realization of the multiplicative operator splitting idea. For certain nonlinear diffusion coefficients with favorable properties, we show that a simple multiple timestep method can improve the diffusion process.     

Gene amplification as a prognostic factor in primary and secondary high-grade malignant gliomas

ND10 are recently characterized nuclear domains that are composed of 0.5 microm sized, precisely circumscribed dots in cultured human cell lines. To investigate the distribution and number of ND10 on various types of normal and neoplastic human tissues, we carried out immunostaining and immunoprecipitation analyses with monoclonal antibodies 138 and 1150. The number of ND10 varied from 1 to 10 or more in various tissues as did their size. ND10 were diffusely located in early embryonic and normal tissues, except for the exocrine and endocrine cells of the pancreas and for hepatocytes. In normal squamous mucosa, basal cells had more ND10 than did differentiated superficial squamous cells. The number and size of ND10 were markedly increased in malignant neoplasms but were similar in benign tumors and corresponding normal tissues. Sex hormone-related normal tissues, such as the endometrium or myometrium, and neoplasms strongly stained for ND10. The distribution pattern of ND10 in human tissues indicates that they are conserved nuclear substructures that are closely associated with cellular differentiation, hormonal stimulation, and oncogenesis.     

Paraneoplastic encephalomyelitis and seminoma: importance of testicular ultrasonography

We report two patients with paraneoplastic limbic and brainstem encephalitis associated with occult nonmetastatic testicular seminoma. In each patient, the neoplasm was detectable only by testicular ultrasonography. Male patients with this syndrome in whom lung cancer is not found should undergo testicular ultrasonography as part of the search for an extrapulmonary neoplasm. A normal clinical testicular examination is insufficient to exclude an occult seminoma.     

Hydrophilic peptides derived from the transframe region of Gag-Pol inhibit the HIV-1 protease

The HIV-1 transframe region (TFR) is between the structural and functional domains of the Gag-Pol polyprotein, flanked by the nucleocapsid and the protease domains at its N and C termini, respectively. Transframe octapeptide (TFP) Phe-Leu-Arg-Glu-Asp-Leu-Ala-Phe, the N terminus of TFR, and its analogues are competitive inhibitors of the action of the mature HIV-1 protease. The smallest, most potent analogues are tripeptides: Glu-Asp-Leu and Glu-Asp-Phe with Ki values of approximately 50 and approximately 20 microM, respectively. Substitution of the acidic amino acids in the TFP by neutral amino acids and d or retro-d configurations of Glu-Asp-Leu results in an >40-fold increase in Ki. Protease inhibition by Glu-Asp-Leu is dependent on a protonated form of a group with a pKa of 3.8; unlike other inhibitors of HIV-1 protease which are highly hydrophobic, Glu-Asp-Leu is extremely soluble in water, and its binding affinity decreases with increasing NaCl concentration. However, Glu-Asp-Leu is a poor inhibitor (Ki approximately 7.5 mM) of the mammalian aspartic acid protease pepsin. X-ray crystallographic studies at pH 4.2 show that the interactions of Glu at P2 and Leu at P1 of Glu-Asp-Leu with residues of the active site of HIV-1 protease are similar to those of other product-enzyme complexes. It was not feasible to understand the interaction of intact TFP with HIV-1 protease under conditions of crystal growth due to its hydrolysis giving rise to two products. The sequence-specific, selective inhibition of the HIV-1 protease by the viral TFP suggests a role for TFP in regulating protease function during HIV-1 replication.     

Equi-affine Invariant Geometry for Shape Analysis

Traditional models of bendable surfaces are based on the exact or approximate invariance to deformations that do not tear or stretch the shape, leaving intact an intrinsic geometry associated with it. These geometries are typically defined using either the shortest path length (geodesic distance), or properties of heat diffusion (diffusion distance) on the surface. Both measures are implicitly derived from the metric induced by the ambient Euclidean space. In this paper, we depart from this restrictive assumption by observing that a different choice of the metric results in a richer set of geometric invariants. We apply equi-affine geometry for analyzing arbitrary shapes with positive Gaussian curvature. The potential of the proposed framework is explored in a range of applications such as shape matching and retrieval, symmetry detection, and computation of Voroni tessellation. We show that in some shape analysis tasks, equi-affine-invariant intrinsic geometries often outperform their Euclidean-based counterparts. We further explore the potential of this metric in facial anthropometry of newborns. We show that intrinsic properties of this homogeneous group are better captured using the equi-affine metric.     

Optical performance characterization of flexible mobile displays

The high interest in the display industry to produce curved or flexible displays for mobile, wearable, and television markets has raised concerns on the performance of displays in their bent state. Flexible display technologies have been developed for this purpose, but their optical characteristics have not been previously reported at various degrees of curvature. The measurement of flexible displays is possible only with special measurement arrangements using common display characterization devices. A conoscope with a working distance of 15 mm was used to demonstrate the curvature dependence of luminance, viewing angle, and color coordinates of the white point of a flexible active‐matrix organic light‐emitting display. The results show that the effect of curvature on the optical characteristics of the display is most evident at the smallest measured bending radii of +/?50 mm and that the effects are most visible when viewing the bent ends of the display, from the central normal vantage point, with uniform curvature along the display.     

Analysis of Two-Dimensional Non-Rigid Shapes

Analysis of deformable two-dimensional shapes is an important problem, encountered in numerous pattern recognition, computer vision and computer graphics applications. In this paper, we address three major problems in the analysis of non-rigid shapes: similarity, partial similarity, and correspondence. We present an axiomatic construction of similarity criteria for deformation-invariant shape comparison, based on intrinsic geometric properties of the shapes, and show that such criteria are related to the Gromov-Hausdorff distance. Next, we extend the problem of similarity computation to shapes which have similar parts but are dissimilar when considered as a whole, and present a construction of set-valued distances, based on the notion of Pareto optimality. Finally, we show that the correspondence between non-rigid shapes can be obtained as a byproduct of the non-rigid similarity problem. As a numerical framework, we use the generalized multidimensional scaling (GMDS) method, which is the numerical core of the three problems addressed in this paper.     

Over-Parameterized Variational Optical Flow

A novel optical flow estimation process based on a spatio-temporal model with varying coefficients multiplying a set of basis functions at each pixel is introduced. Previous optical flow estimation methodologies did not use such an over parameterized representation of the flow field as the problem is ill-posed even without introducing any additional parameters: Neighborhood based methods of the Lucas–Kanade type determine the flow at each pixel by constraining the flow to be described by a few parameters in small neighborhoods. Modern variational methods represent the optic flow directly via the flow field components at each pixel. The benefit of over-parametrization becomes evident in the smoothness term, which instead of directly penalizing for changes in the optic flow, accumulates a cost of deviating from the assumed optic flow model. Our proposed method is very general and the classical variational optical flow techniques are special cases of it, when used in conjunction with constant basis functions. Experimental results with the novel flow estimation process yield significant improvements with respect to the best results published so far.