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检索条件"任意字段=Conference on Image Reconstruction from Incomplete Data V"

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GRADIENT-BASED SURFACE reconstruction USING COMPRESSED SENSING

GRADIENT-BASED SURFACE RECONSTRUCTION USING COMPRESSED SENSI...

引用

IEEE International conference on image Processing

作者： Mohammad Rostami Oleg Michailovich Zhou Wang Department of Electrical & Computer Engineering University of Waterloo Waterloo Canada

Surface reconstruction from measurements of spatial gradient is an important computer vision problem with applications in photometric stereo and shape-from-shading. In the case of morphologically complex surfaces observed in the presence of shadowing and transparency artifacts, a relatively large number of gradient measurements may be required for accurate surface reconstruction. Consequently, due to hardware limitations of image acquisition devices, situations are possible in which the available sampling density might not be sufficiently high to allow for recovery of essential surface details. In this paper, the above problem is resolved by means of derivative compressed sensing (DCS). DCS can be viewed as a modification of the classical compressed sensing (CS), which is particularly suited for reconstructions involving image/surface gradients. We demonstrate that using DCS results in substantial data savings as compared to the standard (dense) sampling, while producing estimates of higher accuracy and smaller variability, as compared to CS-base estimates. The results of this study are further supported by a series of numerical experiments.

关键词： Surface reconstruction image reconstruction Compressed sensing vectors Signal to noise ratio Poisson equations

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Preliminary Results from Attenuation Correction for MCNP-generated PET image

Preliminary Results From Attenuation Correction for MCNP-gen...

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IEEE-EMBS conference on Biomedical Engineering and Sciences

作者： M. Musarudin M. I. Saripan S. Mashohor W. H. M. Saad S. Hashim A. J. Nordin Faculty of Engineering Universiti Putra Malaysia Faculty of Science Universiti Teknologi Malaysia Center of Diagnostic Nuclear Imaging Universiti Putra Malaysia

ISBN: (纸本)9781467316644

This paper presents the preliminary results of PET system simulation using Monte Carlo code. We also present the implementation of attenuation correction for MCNP-generated PET image. Using MCNP5 we constructed a data base for a uniform cylindrical source. The data obtained from the simulation were then used for PET image reconstruction. During the image reconstruction, calculated attenuation correction method was implemented to the PET raw data. This method was chosen due to the fact that our study involved homogeneous and simple geometry phantom.

关键词： Attenuation correction Monte carlo PET

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OCCLUSAL SURFACE reconstruction OF HUMAN TEETH from A SINGLE image BASED ON OBJECT AND SENSOR PHYSICAL CHARACTERISTICS

OCCLUSAL SURFACE RECONSTRUCTION OF HUMAN TEETH FROM A SINGLE...

引用

IEEE International conference on image Processing

作者： Aly Abdelrahim Aly Farag Shireen Elhabian Eslam Mostafa Wael Aboelmaaty Computer Vision and Image Processing Laboratory University of Louisville Louisville KY USA Faculty of Dentistry Mansoura University Egypt Department of Oral Medicine and Periodontology University of Louisville Louisville KY USA

image formation involves understanding sensor characteristics and object reflectance. In dentistry, an accurate 3-D representation of the human jaw may be used for diagnostic and treatment purposes. Photogrammetry can offer a flexible, cost effective solution for accurate 3-D representation of the human teeth, which can be used for diagnostic and treatment purposes. Nonetheless there are several challenges, such as the non-friendly image acquisition environment inside the human mouth, problems with lighting and errors due to the data acquisition sensors. In this paper, we focus on the 3D surface reconstruction aspect for human teeth based on a single image. We introduce a more realistic formulation of the shape-from-shading (SFS) problem by considering the image formation components;the camera, the light source, and the surface reflectance. We propose a non-Lambertian SFS algorithm under perspective projection which benefits from camera calibration parameters. We take into account the attenuation of illumination due to near-field imaging. The surface reflectance is modeled using Oren-Nayar-Wolff model which accounts for the retro-reflection case. Our experiments provide promising quantitative metric results for the proposed approach.

关键词： Teeth Surface reconstruction Rough surfaces Surface roughness Cameras Humans image reconstruction

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QUANTITATIvE MICROWAvE TOMOGRAPHY from SPARSE MEASUREMENTS USING A ROBUST HUBER REGULARIZER

QUANTITATIVE MICROWAVE TOMOGRAPHY FROM SPARSE MEASUREMENTS U...

引用

IEEE International conference on image Processing

作者： F. Bai A. Pizurica S. van Loocke A. Franchois D. De Zutter W. Philips Department of Telecommunications and Information Processing (IPI-TELIN-IBBT) Ghent University Belgium Department of Information Technology (INTEC) Ghent University Belgium

In statistical theory, the Huber function yields robust estimations reducing the effect of outliers. In this paper, we employ the Huber function as regularization in a challenging inverse problem: quantitative microwave imaging. Quantitative microwave tomography aims at estimating the permittivity profile of a scattering object based on measured scattered fields, which is a nonlinear, ill-posed inverse problem. The results on 3D data sets are encouraging: the reconstruction error is reduced and the permittivity profile can be estimated from fewer measurements compared to state-of-the art inversion procedures.

关键词： Permittivity Microwave imaging Microwave measurements Microwave theory and techniques Antenna measurements Inverse problems image reconstruction

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NON-RIGID STRUCTURE from MOTION WITH INCREMENTAL SHAPE PRIOR

NON-RIGID STRUCTURE FROM MOTION WITH INCREMENTAL SHAPE PRIOR

引用

IEEE International conference on image Processing

作者： Lili Tao Bogdan J. Matuszewski Stephen J. Mein Applied Digital Signal and Image Processing Research Centre University of Central Lancashire Preston UK

Most existing approaches to the non-rigid structure from motion problem use batch type algorithms with all the data collected before 3D shape reconstruction takes place. Such a methodology is not suitable for real-time applications. Concurrent on-line estimation of the camera position and 3D structure, based only on the measurements up to that moment is much more a challenging problem. In this paper, a novel approach is proposed for recursive recovery of non-rigid structures from image sequences captured by an orthographic camera. The main novelty in the proposed method is an adaptive algorithm for construction of shape constraints imposing stability on the on-line reconstructed shapes. The proposed, adaptively learned constraints have two aspects, consisting of constraints imposed on the basic shapes, the basic "building blocks" from which shapes are reconstructed, as well as constraints imposed on the mixing coefficients in a form of their probability distribution. The constraints are updated when the current model inadequately represents new shapes. This is achieved by means of Incremental Principal Component Analysis (IPCA). Results of the proposed method are shown on synthetic and real data of articulated face.

关键词： Shape image reconstruction Principal component analysis Cameras Face vectors Optimization

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Spatial Interpolation using Multiple Regression

Spatial Interpolation using Multiple Regression

引用

IEEE International conference on data Mining

作者： Orlando Ohashi Luis Torgo LIAAD - INESC TEC/DCC Faculdade de Ciencias - Universidade do Porto

ISBN: (纸本)9781467346498

Many real world data mining applications involve analyzing geo-referenced data. Frequently, this type of data sets are incomplete in the sense that not all geographical coordinates have measured values of the variable(s) of interest. This incompleteness may be caused by poor data collection, measurement errors, costs management and many other factors. These missing values may cause several difficulties in many applications. Spatial imputation/interpolation methods try to fill in these unknown values in geo-referenced data sets. In this paper we propose a new spatial imputation method based on machine learning algorithms and a series of data preprocessing steps. The key distinguishing factor of this method is allowing the use of data from faraway regions, contrary to the state of the art on spatial data mining. images (e.g. from a satellite or video surveillance cameras) may also suffer from this incompleteness where some pixels are missing, which again may be caused by many factors. An image can be seen as a spatial data set in a Cartesian coordinates system, where each pixel (location) registers some value (e.g. degree of gray on a black and white image). Being able to recover the original image from a partial or incomplete version of the reality is a key application in many domains (e.g. surveillance, security, etc.). In this paper we evaluate our general methodology for spatial interpolation on this type of problems. Namely, we check the ability of our method to fill in unknown pixels on several images. We compare it to state of the art methods and provide strong experimental evidence of the advantages of our proposal.

关键词： Spatial prediction data pre-processing

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JOINT DEMOSAICKING AND DENOISING BY TOTAL vARIATION MINIMIZATION

JOINT DEMOSAICKING AND DENOISING BY TOTAL VARIATION MINIMIZA...

引用

IEEE International conference on image Processing

作者： Laurent Condat Saleh Mosaddegh GREYC joint research unit of the CNRS ENSICAEN University Caen Basse-Normandie Caen France

Joint demosaicking and denoising consists in reconstructing a color image from the noisy raw data output by the sensor of a digital camera. We adopt a variational formulation in which the reconstructed image has minimal total variation under the constraint of consistency with the available measurements. This way, the recovered color image has smooth chrominance but the sharp edges are maintained and the noise is transferred to the luminance channel. This channel is de-noised subsequently.

关键词： image color analysis Color Noise reduction image reconstruction Noise measurement Colored noise

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A Comparison of the Options for Brain Partial volume Correction Using PET/MRI

A Comparison of the Options for Brain Partial Volume Correct...

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IEEE Nuclear Science Symposium and Medical Imaging conference

作者： Benjamin A. Thomas Kjell Erlandsson Anthonin Reilhac Alexandre Bousse Daniil Kazantsev Stefano Pedemonte Kathleen vunckx Simon Arridge Sebastien Ourselin Brian F. Hutton Institute of Nuclear Medicine University College London Department of Life Sciences Australian Nuclear Science Organization Centre for Medical Image Computing University College London Department of Nuclear Medicine Katholieke Universiteit Leuven

ISBN: (纸本)9781467320283

Partial volume effects affect the quantitative accuracy of PET images. Many approaches to partial volume correction (PvC) have been proposed, however most rely on additional, patient-specific anatomical information from structural imaging modalities such as MRI. In order to utilize anatomical data, image registration is required. With the recent advent of simultaneous PET/MRI scanners comes the ability to acquire accurately registered data. In this study, applied eight different PvC techniques to Monte Carlo simulated data, derived from a clinical brain FDG PET/MRI study. reconstruction-based and post-reconstruction PvC methods were evaluated. Their performance was investigated in terms of bias vs. noise, lesion contrast and when faced with registration errors. Excellent quantification, with reduced noise, can be achieved by applying PvC when accurately aligned data are available. reconstruction-based methods produced images with low bias and reduced noise. Post-reconstruction techniques appeared to be more sensitive to registration and segmentation errors. All PvC techniques improved recovery compared to the uncorrected data.

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A FULLY ROBUST FRAMEWORK FOR MAP image SUPER-RESOLUTION

A FULLY ROBUST FRAMEWORK FOR MAP IMAGE SUPER-RESOLUTION

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IEEE International conference on image Processing

作者： Michalis vrigkas Christophoros Nikou Lisimachos P. Kondi Department of Computer Science University of Ioannina Greece

In this work, we propose an adaptive M-estimation scheme for robust image super-resolution. The proposed algorithm relies on a maximum a posteriori (MAP) framework and addresses the presence of outliers in the low resolution images. Moreover, apart from the robust estimation of the high resolution image, the contribution of the method is twofold: (i) the robust computation of the regularization parameters controlling the relative strength of the prior with respect to the data fidelity term and (ii) the robust estimation of the optimal step size in the update of the high resolution image. Experimental results demonstrate that integrating these estimations into a robust framework leads to significant improvement in the accuracy of the high resolution image.

关键词： Robustness Estimation Signal resolution image reconstruction Spatial resolution Standards

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Temperature-field reconstruction for the application of prostate cryosurgery

Temperature-field reconstruction for the application of pros...

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Annual Northeast Bioengineering conference

作者： C. v. Thaokar Y. Rabin Biothermal Technology Laboratory Department of Mechanical Engineering Carnegie Mellon University Pittsburgh PA USA

This study is a part of an ongoing effort to develop means to monitor the temperature field during minimally invasive cryosurgery - the destruction of undesired tissues by freezing. In particular, this study focuses on developing a method for temperature-field reconstruction based on data obtained from an array of wireless implantable temperature sensors. Results of this study indicate that the implantable sensors can potentially improve cryosurgery monitoring. Results of this study further demonstrate that the location of the lethal temperature can be identified, which represents an unmet need in current cryosurgery practice.

关键词： Temperature sensors Temperature distribution image reconstruction Ultrasonic imaging Imaging Temperature measurement

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