Super-resolution of remotely sensed images with variable-pixel linear reconstruction

This paper describes the development and applications of a super-resolution method, known as Super-Resolution Variable-Pixel Linear Reconstruction. The algorithm works combining different lower resolution images in order to obtain, as a result, a higher resolution image. We show that it can make significant spatial resolution improvements to satellite images of the Earth¿s surface allowing recognition of objects with size approaching the limiting spatial resolution of the lower resolution images. The algorithm is based on the Variable-Pixel Linear Reconstruction algorithm developed by Fruchter and Hook, a well-known method in astronomy but never used for Earth remote sensing purposes. The algorithm preserves photometry, can weight input images according to the statistical significance of each pixel, and removes the effect of geometric distortion on both image shape and photometry. In this paper, we describe its development for remote sensing purposes, show the usefulness of the algorithm working with images as different to the astronomical images as the remote sensing ones, and show applications to: 1) a set of simulated multispectral images obtained from a real Quickbird image; and 2) a set of multispectral real Landsat Enhanced Thematic Mapper Plus (ETM+) images. These examples show that the algorithm provides a substantial improvement in limiting spatial resolution for both simulated and real data sets without significantly altering the multispectral content of the input low-resolution images, without amplifying the noise, and with very few artifacts.

Quality of assessement of CMR images in the setting of the European cardiovascular magnetic resonance registry : description and validation of standardized criteria

l'imagerie par résonance magnétique (IRMC) est une technologie utilisée depuis les aimées quatre¬-vingts dans le monde de la cardiologie. Cette technique d'imagerie non-invasive permet d'acquérir Ses images du coeur en trois dimensions, dans n'importe quel, plan, sans application de radiation, et en haute résolution. Actuellement, cette technique est devenue un référence dans l'évaluation et 'l'investigation de différentes pathologies cardiaques. La morphologie cardiaque, la fonction des ventricules ainsi que leur contraction, la perfusion tissulaire ainsi que la viabilité tissulaire peuvent être caractérisés en utilisant différentes séquences d'imagerie. Cependant, cette technologie repose sur des principes physiques complexes et la mise en pratique de cette technique se heurte à la difficulté d'évaluer un organe en mouvement permanent. L'IRM cardiaque est donc sujette à différents artefacts qui perturbent l'interprétation des examens et peuvent diminuer la précision diagnostique de cette technique. A notre connaissance, la plupart des images d'IRMC sont analysées et interprétées sans évaluation rigoureuse de la qualité intrinsèque de l'examen. Jusqu'à présent, et à notre connaissance, aucun critère d'évaluation de la qualité des examens d'IRMC n'a été clairement déterminé. L'équipe d'IRMC du CHUV, dirigée par le Prof J. Schwitter, a recensé une liste de 35 critères qualitatifs et 12 critères quantitatifs évaluant la qualité d'un examen d'IRMC et les a introduit dans une grille d'évaluation. L'objet de cette étude est de décrire et de valider la reproductibilité des critères figurant dans cette grille d'évaluation, par l'interprétation simultanée d'examens IRMC par différents observateurs (cardiologues spécialisés en IRM, étudiant en médecine, infirmière spécialisée). Notre étude a permis de démontrer que les critères définis pour l'évaluation des examens d'IRMC sont robustes, et permettent une bonne reproductibilité intra- et inter-observateurs. Cette étude valide ainsi l'utilisation de ces critères de qualité dans le cadre de l'imagerie par résonance magnétique cardiaque. D'autres études sont encore nécessaires afin de déterminer l'impact de la qualité de l'image sur la précision diagnostique de cette technique. Les critères standardisés que nous avons validés seront utilisés pour évaluer la qualité des images dans le cadre d'une étude à échelle européenne relative à l'IRMC : "l'EuroCMR registry". Parmi les autres utilités visées par ces critères de qualité, citons notamment la possibilité d'avoir une référence d'évaluation de la qualité d'examen pour toutes les futures études cliniques utilisant la technologie d'IRMC, de permettre aux centres d'IRMC de quantifier leur niveau de qualité, voire de créer un certificat de standard de qualité pour ces centres, d'évaluer la reproductibilité de l'évaluation des images par différents observateurs d'un même centre, ou encore d'évaluer précisément la qualité des séquences développées à l'avenir dans le monde de l'IRMC.

Brain Surface Segmentation of Magnetic Resonance Images of the Fetus

In this work we present a method for the image analysisof Magnetic Resonance Imaging (MRI) of fetuses. Our goalis to segment the brain surface from multiple volumes(axial, coronal and sagittal acquisitions) of a fetus. Tothis end we propose a two-step approach: first, a FiniteGaussian Mixture Model (FGMM) will segment the image into3 classes: brain, non-brain and mixture voxels. Second, aMarkov Random Field scheme will be applied tore-distribute mixture voxels into either brain ornon-brain tissue. Our main contributions are an adaptedenergy computation and an extended neighborhood frommultiple volumes in the MRF step. Preliminary results onfour fetuses of different gestational ages will be shown.

Correlation postprocessing-based method for the detection of de focused images

We present a method to detect patterns in defocused scenes by means of a joint transform correlator. We describe analytically the correlation plane, and we also introduce an original procedure to recognize the target by postprocessing the correlation plane. The performance of the methodology when the defocused images are corrupted by additive noise is also considered.

Reconstructing images from their most singular fractal manifold

Real-world images are complex objects, difficult to describe but at the same time possessing a high degree of redundancy. A very recent study [1] on the statistical properties of natural images reveals that natural images can be viewed through different partitions which are essentially fractal in nature. One particular fractal component, related to the most singular (sharpest) transitions in the image, seems to be highly informative about the whole scene. In this paper we will show how to decompose the image into their fractal components.We will see that the most singular component is related to (but not coincident with) the edges of the objects present in the scenes. We will propose a new, simple method to reconstruct the image with information contained in that most informative component.We will see that the quality of the reconstruction is strongly dependent on the capability to extract the relevant edges in the determination of the most singular set.We will discuss the results from the perspective of coding, proposing this method as a starting point for future developments.

Multi-Atlas based Segmentation of Head and Neck CT Images using Active Contour

This paper presents the segmentation of bilateral parotid glands in the Head and Neck (H&N) CT images using an active contour based atlas registration. We compare segmentation results from three atlas selection strategies: (i) selection of "single-most-similar" atlas for each image to be segmented, (ii) fusion of segmentation results from multiple atlases using STAPLE, and (iii) fusion of segmentation results using majority voting. Among these three approaches, fusion using majority voting provided the best results. Finally, we present a detailed evaluation on a dataset of eight images (provided as a part of H&N auto segmentation challenge conducted in conjunction with MICCAI-2010 conference) using majority voting strategy.

Self-similarity properties of natural images resemble those of turbulent flows

We show that the statistics of an edge type variable in natural images exhibits self-similarity properties which resemble those of local energy dissipation in turbulent flows. Our results show that self-similarity and extended self-similarity hold remarkably for the statistics of the local edge variance, and that the very same models can be used to predict all of the associated exponents. These results suggest using natural images as a laboratory for testing more elaborate scaling models of interest for the statistical description of turbulent flows. The properties we have exhibited are relevant for the modeling of the early visual system: They should be included in models designed for the prediction of receptive fields.

Multifractal wavelet filter of natural images

Natural images are characterized by the multiscaling properties of their contrast gradient, in addition to their power spectrum. In this Letter we show that those properties uniquely define an intrinsic wavelet and present a suitable technique to obtain it from an ensemble of images. Once this wavelet is known, images can be represented as expansions in the associated wavelet basis. The resulting code has the remarkable properties that it separates independent features at different resolution level, reducing the redundancy, and remains essentially unchanged under changes in the power spectrum. The possible generalization of this representation to other systems is discussed.

Multiscaling and information content of natural color images

Naive scale invariance is not a true property of natural images. Natural monochrome images possess a much richer geometrical structure, which is particularly well described in terms of multiscaling relations. This means that the pixels of a given image can be decomposed into sets, the fractal components of the image, with well-defined scaling exponents [Turiel and Parga, Neural Comput. 12, 763 (2000)]. Here it is shown that hyperspectral representations of natural scenes also exhibit multiscaling properties, observing the same kind of behavior. A precise measure of the informational relevance of the fractal components is also given, and it is shown that there are important differences between the intrinsically redundant red-green-blue system and the decorrelated one defined in Ruderman, Cronin, and Chiao [J. Opt. Soc. Am. A 15, 2036 (1998)].