992 resultados para image fusion


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Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs) are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT) was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC) algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion). Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM) algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE) and better distribution of feature points.

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Image acquisition systems based on multi-head arrangement of digital camerasare attractive alternatives enabling a larger imaging area when compared to a single framecamera. The calibration of this kind of system can be performed in several steps or byusing simultaneous bundle adjustment with relative orientation stability constraints. Thepaper will address the details of the steps of the proposed approach for system calibration,image rectification, registration and fusion. Experiments with terrestrial and aerial imagesacquired with two Fuji FinePix S3Pro cameras were performed. The experiments focusedon the assessment of the results of self-calibrating bundle adjustment with and withoutrelative orientation constraints and the effects to the registration and fusion when generatingvirtual images. The experiments have shown that the images can be accurately rectified andregistered with the proposed approach, achieving residuals smaller than one pixel. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

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The purpose of this study is to develop and evaluate techniques that improve the spatial resolution of the channels already selected in the preliminary studies for Geostationary Observatory for Microwave Atmospheric Soundings (GOMAS). Reference high resolution multifrequency brightness temperatures scenarios have been derived by applying radiative transfer calculation to the spatially and microphysically detailed output of meteorological events simulated by the University of Wisconsin - Non-hydrostatic Model System (UW-NMS). Three approaches, Wiener filter, Super-Resolution and Image Fusion have been applied to some representative GOMAS frequency channels to enhance the resolution of antenna temperatures. The Wiener filter improved resolution of the largely oversampled images by a factor 1.5- 2.0 without introducing any penalty in the radiometric accuracy. Super-resolution, suitable for not largely oversampled images, improved resolution by a factor ~1.5 but introducing an increased radiometric noise by a factor 1.4-2.5. The image fusion allows finally to further increase the spatial frequency of the images obtained by the Wiener filter increasing the total resolution up to a factor 5.0 with an increased radiometric noise closely linked to the radiometric frequency and to the examined case study.

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A causa della limitata estensione del campo di vista del sistema, con un microscopio ottico tradizionale non è possibile acquisire una singola immagine completamente a fuoco se l’oggetto è caratterizzato da una profondità non trascurabile. Fin dagli anni ’70, il problema dell’estensione della profondità di fuoco è stato ampiamente trattato in letteratura e molti metodi sono stati proposti per superare questo limite. Tuttavia, è molto difficile riuscire a decretare quale metodo risulti essere il migliore in una specifica applicazione, a causa della mancanza di una metrica validata e adatta ad essere utilizzata anche in casi reali, dove generalmente non si ha a disposizione un’immagine di riferimento da considerare come “la verità” (ground truth). L’Universal Quality Index (UQI) è ampiamente utilizzato in letteratura per valutare la qualità dei risultati in processi di elaborazione di immagini. Tuttavia, per poter calcolare questo indice è necessaria una ground truth. In effetti, sono state proposte in letteratura alcune estensioni dell’UQI per valutare il risultato dei metodi di fusione anche senza immagine di riferimento, ma nessuna analisi esaustiva è stata proposta per dimostrare la loro equivalenza con l’UQI standard nel valutare la qualità di un’immagine. In questo lavoro di Tesi, partendo dai limiti dei metodi attualmente utilizzati per l'estensione della profondità di campo di un microscopio, ed esposti in letteratura, per prima cosa è stato proposto un nuovo metodo, basato su approccio spaziale e fondato su analisi locale del segnale appositamente filtrato. Attraverso l’uso di sequenze di immagini sintetiche, delle quali si conosce la ground truth, è stato dimostrato, utilizzando metriche comuni in image processing, che il metodo proposto è in grado di superare le performance dei metodi allo stato dell'arte. In seguito, attraverso una serie di esperimenti dedicati, è stato provato che metriche proposte e ampiamente utilizzate in letteratura come estensione dell'UQI per valutare la qualità delle immagini prodotte da processi di fusione, sebbene dichiarate essere sue estensioni, non sono in grado di effettuare una valutazione quale quella che farebbe l'UQI standard. E’ quindi stato proposto e validato un nuovo approccio di valutazione che si è dimostrato in grado di classificare i metodi di fusione testati così come farebbe l’UQI standard, ma senza richiedere un’immagine di riferimento. Infine, utilizzando sequenze di immagini reali acquisite a differenti profondità di fuoco e l’approccio di valutazione validato, è stato dimostrato che il metodo proposto per l’estensione della profondità di campo risulta sempre migliore, o almeno equivalente, ai metodi allo stato dell’arte.

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What's known on the subject? And what does the study add? We have previously shown that percutaneous radiofrequency ablation guided by image-fusion technology allows for precise needle placement with real time ultrasound superimposed with pre-loaded imaging, removing the need for real-time CT or MR guidance. Emerging technology also allows real-time tracking of a treatment needle within an organ in a virtually created 3D format. To our knowledge, this is the first study utilising a sophisticated ultrasound-based navigation system that uses both image-fusion and real-time probe-tracking technologies for in-vivo renal ablative intervention.

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OBJECTIVE Angiographic C-arm CT may allow performing percutaneous stereotactic tumor ablations in the interventional radiology suite. Our purpose was to evaluate the accuracy of using C-arm CT for single and multimodality image fusions and to compare the targeting accuracy of liver lesions with the reference standard of MDCT. MATERIALS AND METHODS C-arm CT and MDCT scans were obtained of a nonrigid rapid prototyping liver phantom containing five 1-mm targets that were placed under skin-simulating deformable plastic foam. Target registration errors of image fusion were evaluated for single-modality and multimodality image fusions. A navigation system and stereotactic aiming device were used to evaluate target positioning errors on postinterventional scans with the needles in place fused with the C-arm CT or MDCT planning images. RESULTS Target registration error of the image fusion showed no significant difference (p > 0.05) between both modalities. In five series with a total of 25 punctures for each modality, the lateral target positioning error (i.e., the lateral distance between the needle tip and the planned trajectory) was similar for C-arm CT (mean [± SD], 1.6 ± 0.6 mm) and MDCT (1.82 ± .97 mm) (p = 0.33). CONCLUSION In a nonrigid liver phantom, angiographic C-arm CT may provide similar image fusion accuracy for comparison of intra- and postprocedure control images with the planning images and enables stereotactic targeting accuracy similar to that of MDCT.

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PURPOSE Digital developments have led to the opportunity to compose simulated patient models based on three-dimensional (3D) skeletal, facial, and dental imaging. The aim of this systematic review is to provide an update on the current knowledge, to report on the technical progress in the field of 3D virtual patient science, and to identify further research needs to accomplish clinical translation. MATERIALS AND METHODS Searches were performed electronically (MEDLINE and OVID) and manually up to March 2014 for studies of 3D fusion imaging to create a virtual dental patient. Inclusion criteria were limited to human studies reporting on the technical protocol for superimposition of at least two different 3D data sets and medical field of interest. RESULTS Of the 403 titles originally retrieved, 51 abstracts and, subsequently, 21 full texts were selected for review. Of the 21 full texts, 18 studies were included in the systematic review. Most of the investigations were designed as feasibility studies. Three different types of 3D data were identified for simulation: facial skeleton, extraoral soft tissue, and dentition. A total of 112 patients were investigated in the development of 3D virtual models. CONCLUSION Superimposition of data on the facial skeleton, soft tissue, and/or dentition is a feasible technique to create a virtual patient under static conditions. Three-dimensional image fusion is of interest and importance in all fields of dental medicine. Future research should focus on the real-time replication of a human head, including dynamic movements, capturing data in a single step.

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OBJECTIVES The aim of this Short Communication was to present a workflow for the superimposition of intraoral scan (IOS), cone-beam computed tomography (CBCT), and extraoral face scan (EOS) creating a 3D virtual dental patient. MATERIAL AND METHODS As a proof-of-principle, full arch IOS, preoperative CBCT, and mimic EOS were taken and superimposed to a unique 3D data pool. The connecting link between the different files was to detect existing teeth as constant landmarks in all three data sets. RESULTS This novel application technique successfully demonstrated the feasibility of building a craniofacial virtual model by image fusion of IOS, CBCT, and EOS under 3D static conditions. CONCLUSIONS The presented application is the first approach that realized the fusion of intraoral and facial surfaces combined with skeletal anatomy imaging. This novel 3D superimposition technique allowed the simulation of treatment planning, the exploration of the patients' expectations, and the implementation as an effective communication tool. The next step will be the development of a real-time 4D virtual patient in motion.

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Most fusion satellite image methodologies at pixel-level introduce false spatial details, i.e.artifacts, in the resulting fusedimages. In many cases, these artifacts appears because image fusion methods do not consider the differences in roughness or textural characteristics between different land covers. They only consider the digital values associated with single pixels. This effect increases as the spatial resolution image increases. To minimize this problem, we propose a new paradigm based on local measurements of the fractal dimension (FD). Fractal dimension maps (FDMs) are generated for each of the source images (panchromatic and each band of the multi-spectral images) with the box-counting algorithm and by applying a windowing process. The average of source image FDMs, previously indexed between 0 and 1, has been used for discrimination of different land covers present in satellite images. This paradigm has been applied through the fusion methodology based on the discrete wavelet transform (DWT), using the à trous algorithm (WAT). Two different scenes registered by optical sensors on board FORMOSAT-2 and IKONOS satellites were used to study the behaviour of the proposed methodology. The implementation of this approach, using the WAT method, allows adapting the fusion process to the roughness and shape of the regions present in the image to be fused. This improves the quality of the fusedimages and their classification results when compared with the original WAT method

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La teledetección o percepción remota (remote sensing) es la ciencia que abarca la obtención de información (espectral, espacial, temporal) sobre un objeto, área o fenómeno a través del análisis de datos adquiridos por un dispositivo que no está en contacto con el elemento estudiado. Los datos obtenidos a partir de la teledetección para la observación de la superficie terrestre comúnmente son imágenes, que se caracterizan por contar con un sinnúmero de aplicaciones que están en continua evolución, por lo cual para solventar los constantes requerimientos de nuevas aplicaciones a menudo se proponen nuevos algoritmos que mejoran o facilitan algún proceso en particular. Para el desarrollo de dichos algoritmos, es preciso hacer uso de métodos matemáticos que permitan la manipulación de la información con algún fin específico. Dentro de estos métodos, el análisis multi-resolución se caracteriza por permitir analizar una señal en diferentes escalas, lo que facilita trabajar con datos que puedan tener resoluciones diferentes, tal es el caso de las imágenes obtenidas mediante teledetección. Una de las alternativas para la implementación de análisis multi-resolución es la Transformada Wavelet Compleja de Doble Árbol (DT-CWT). Esta transformada se implementa a partir de dos filtros reales y se caracteriza por presentar invariancia a traslaciones, precio a pagar por su característica de no ser críticamente muestreada. A partir de las características de la DT-CWT se propone su uso en el diseño de algoritmos de procesamiento de imagen, particularmente imágenes de teledetección. Estos nuevos algoritmos de procesamiento digital de imágenes de teledetección corresponden particularmente a fusión y detección de cambios. En este contexto esta tesis presenta tres algoritmos principales aplicados a fusión, evaluación de fusión y detección de cambios en imágenes. Para el caso de fusión de imágenes, se presenta un esquema general que puede ser utilizado con cualquier algoritmo de análisis multi-resolución; este algoritmo parte de la implementación mediante DT-CWT para luego extenderlo a un método alternativo, el filtro bilateral. En cualquiera de los dos casos la metodología implica que la inyección de componentes pueda realizarse mediante diferentes alternativas. En el caso del algoritmo de evaluación de fusión se presenta un nuevo esquema que hace uso de procesos de clasificación, lo que permite evaluar los resultados del proceso de fusión de forma individual para cada tipo de cobertura de uso de suelo que se defina en el proceso de evaluación. Esta metodología permite complementar los procesos de evaluación tradicionales y puede facilitar el análisis del impacto de la fusión sobre determinadas clases de suelo. Finalmente, los algoritmos de detección de cambios propuestos abarcan dos enfoques. El primero está orientado a la obtención de mapas de sequía en datos multi-temporales a partir de índices espectrales. El segundo enfoque propone la utilización de un índice global de calidad espectral como filtro espacial. La utilización de dicho filtro facilita la comparación espectral global entre dos imágenes, esto unido a la utilización de umbrales, conlleva a la obtención de imágenes diferencia que contienen la información de cambio. ABSTRACT Remote sensing is a science relates to information gathering (spectral, spatial, temporal) about an object, area or phenomenon, through the analysis of data acquired by a device that is not in contact with the studied item. In general, data obtained from remote sensing to observe the earth’s surface are images, which are characterized by having a number of applications that are constantly evolving. Therefore, to solve the constant requirements of applications, new algorithms are proposed to improve or facilitate a particular process. With the purpose of developing these algorithms, each application needs mathematical methods, such as the multiresolution analysis which allows to analyze a signal at different scales. One of the options is the Dual Tree Complex Wavelet Transform (DT-CWT) which is implemented from two real filters and is characterized by invariance to translations. Among the advantages of this transform is its successful application in image fusion and change detection areas. In this regard, this thesis presents three algorithms applied to image fusion, assessment for image fusion and change detection in multitemporal images. For image fusion, it is presented a general outline that can be used with any multiresolution analysis technique; this algorithm is proposed at first with DT-CWT and then extends to an alternative method, the bilateral filter. In either case the method involves injection of components by various means. For fusion assessment, the proposal is focused on a scheme that uses classification processes, which allows evaluating merger results individually for each type of land use coverage that is defined in evaluation process. This methodology allows complementing traditional assessment processes and can facilitate impact analysis of the merger on certain kinds of soil. Finally, two approaches of change detection algorithms are included. The first is aimed at obtaining drought maps in multitemporal data from spectral indices. The second one takes a global index of spectral quality as a spatial filter. The use of this filter facilitates global spectral comparison between two images and by means of thresholding, allows imaging containing change information.

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The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.