Download or read book On the Bayesian Approach to Image Reconstruction written by Gabor T. Herman and published by . This book was released on 1978 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Image Reconstruction written by and published by . This book was released on 1989 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we propose a Maximum a Posteriori (MAP) method of image reconstruction in the Bayesian framework for the Poisson noise case. We use entropy to define the prior probability and likelihood to define the conditional probability. The method uses sharpness parameters which can be theoretically computed or adjusted, allowing us to obtain MAP reconstructions without the problem of the grey'' reconstructions associated with the pre Bayesian reconstructions. We have developed several ways to solve the reconstruction problem and propose a new iterative algorithm which is stable, maintains positivity and converges to feasible images faster than the Maximum Likelihood Estimate method. We have successfully applied the new method to the case of Emission Tomography, both with simulated and real data. 41 refs., 4 figs., 1 tab.

Download or read book Bayesian Approach to Image Interpretation written by Sunil K. Kopparapu and published by Springer Science & Business Media. This book was released on 2005-11-25 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existing probabilistic methods for image interpretation and presents some new results. Additionally, there is extensive bibliography covering references in varied areas. For a researcher in this field, the material on synergistic integration of segmentation and interpretation modules and the Bayesian approach to image interpretation will be beneficial. For a practicing engineer, the procedure for generating knowledge base, selecting initial temperature for the simulated annealing algorithm, and some implementation issues will be valuable. New ideas introduced in the book include: New approach to image interpretation using synergism between the segmentation and the interpretation modules. A new segmentation algorithm based on multiresolution analysis. Novel use of the Bayesian networks (causal networks) for image interpretation. Emphasis on making the interpretation approach less dependent on the knowledge base and hence more reliable by modeling the knowledge base in a probabilistic framework. Useful in both the academic and industrial research worlds, Bayesian Approach to Image Interpretation may also be used as a textbook for a semester course in computer vision or pattern recognition.

Download or read book A Bayesian Approach to High Resolution 3D Surface Reconstruction from Multiple Images written by Robin D. Morris and published by . This book was released on 1999 with total page 4 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "We present a radically different approach to the recovery of the three dimensional geometric and reflectance properties of a surface from image data. We pose the problem in a Bayesian framework, and proceed to infer the parameters of the model describing the surface. This allows great flexibility in the specification of the model, in terms of how both the geometrical properties and surface reflectance are specified. In the usual manner for Bayesian approaches it requires that we can simulate the data that would have been recorded for any state of the model in order to infer the model. The theoretical aspects are thus very general. We present results for one type of surface geometry (the triangular mesh) and for the Lambertian model of light scattering. Our framework also allows the easy incorporation of data from multiple sensing modalities."

Download or read book Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing written by Jean-Francois Giovannelli and published by John Wiley & Sons. This book was released on 2015-02-16 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on the basis of observed data. The building of solutions involves the recognition of other pieces of a priori information. These solutions are then specific to the pieces of information taken into account. Clarifying and taking these pieces of information into account is necessary for grasping the domain of validity and the field of application for the solutions built. For too long, the interest in these problems has remained very limited in the signal-image community. However, the community has since recognized that these matters are more interesting and they have become the subject of much greater enthusiasm. From the application field’s point of view, a significant part of the book is devoted to conventional subjects in the field of inversion: biological and medical imaging, astronomy, non-destructive evaluation, processing of video sequences, target tracking, sensor networks and digital communications. The variety of chapters is also clear, when we examine the acquisition modalities at stake: conventional modalities, such as tomography and NMR, visible or infrared optical imaging, or more recent modalities such as atomic force imaging and polarized light imaging.

Download or read book A Bayesian Approach to High Resolution Three dimensional Surface Reconstruction from Multiple Images written by Research Institute for Advanced Computer Science (U.S.) and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Approach to Inverse Problems written by Jérôme Idier and published by John Wiley & Sons. This book was released on 2013-03-01 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many scientific, medical or engineering problems raise the issue of recovering some physical quantities from indirect measurements; for instance, detecting or quantifying flaws or cracks within a material from acoustic or electromagnetic measurements at its surface is an essential problem of non-destructive evaluation. The concept of inverse problems precisely originates from the idea of inverting the laws of physics to recover a quantity of interest from measurable data. Unfortunately, most inverse problems are ill-posed, which means that precise and stable solutions are not easy to devise. Regularization is the key concept to solve inverse problems. The goal of this book is to deal with inverse problems and regularized solutions using the Bayesian statistical tools, with a particular view to signal and image estimation. The first three chapters bring the theoretical notions that make it possible to cast inverse problems within a mathematical framework. The next three chapters address the fundamental inverse problem of deconvolution in a comprehensive manner. Chapters 7 and 8 deal with advanced statistical questions linked to image estimation. In the last five chapters, the main tools introduced in the previous chapters are put into a practical context in important applicative areas, such as astronomy or medical imaging.

Download or read book A Bayesian Approach to Image Restoration and Segmentation written by P.E. Duroux and published by . This book was released on 1990 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introduction to Bayesian Image Analysis written by and published by . This book was released on 1993 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt: The basic concepts in the application of Bayesian methods to image analysis are introduced. The Bayesian approach has benefits in image analysis and interpretation because it permits the use of prior knowledge concerning the situation under study. The fundamental ideas are illustrated with a number of examples ranging from a problem in one and two dimensions to large problems in image reconstruction that make use of sophisticated prior information.

Download or read book Patch based Bayesian Approaches for Image Restoration written by Dai viet Tran and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we investigate the patch-based image denoising and super-resolution under the Bayesian Maximum A Posteriori framework, with the help of a set of high quality images which are known as standard images. Our contributions are to address the construction of the dictionary, which is used to represent image patches, and the prior distribution in dictionary space. We have demonstrated that the careful selection of dictionary to represent the local information of image can improve the image reconstruction. By establishing an exhaustive dictionary from the standard images, our main attribute is to locally select a sub-dictionary of matched patches to recover each patch in the degraded image. Beside the conventional Euclidean measure, we propose an effective similarity metric based on the Earth Mover's Distance (EMD) for image patch-selection by considering each patch as a distribution of image intensities. Our EMD-based super-resolution algorithm has outperformed comparing to some state-of-the-art super-resolution methods.To enhance the quality of image denoising, we exploit the distribution of patches in the dictionary space as a an image prior to regularize the optimization problem. We develop a computationally efficient procedure, based on piece-wise constant function estimation, for low dimension dictionaries and then proposed a Gaussian Mixture Model (GMM) for higher complexity dictionary spaces. Finally, we justify the practical number of Gaussian components required for recovering patches. Our researches on multiple datasets with combination of different dictionaries and GMM models have complemented the lack of evidence of using GMM in the literature.

Download or read book A computer implementation of a bayesian analysis of image reconstruction written by State University of New York at Buffalo. Dept. of Computer Science and published by . This book was released on 1974 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Image Reconstruction Using Image modeling Gibbs Priors written by Michael T. Chan and published by . This book was released on 1995 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book From Signals to Image written by Haim Azhari and published by Springer Nature. This book was released on 2020-05-29 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook, intended for advanced undergraduate and graduate students, is an introduction to the physical and mathematical principles used in clinical medical imaging. The first two chapters introduce basic concepts and useful terms used in medical imaging and the tools implemented in image reconstruction, while the following chapters cover an array of topics such as physics of x-rays and their implementation in planar and computed tomography (CT) imaging; nuclear medicine imaging and the methods of forming functional planar and single photon emission computed tomography (SPECT) images and Clinical imaging using positron emitters as radiotracers. The book also discusses the principles of MRI pulse sequencing and signal generation, gradient fields, and the methodologies implemented for image formation, form flow imaging and magnetic resonance angiography and the basic physics of acoustic waves, the different acquisition modes used in medical ultrasound, and the methodologies implemented for image formation and flow imaging using the Doppler Effect. By the end of the book, readers will know what is expected from a medical image, will comprehend the issues involved in producing and assessing the quality of a medical image, will be able to conceptually implement this knowledge in the development of a new imaging modality, and will be able to write basic algorithms for image reconstruction. Knowledge of calculus, linear algebra, regular and partial differential equations, and a familiarity with the Fourier transform and it applications is expected, along with fluency with computer programming. The book contains exercises, homework problems, and sample exam questions that are exemplary of the main concepts and formulae students would encounter in a clinical setting.

Download or read book Medical Image Reconstruction written by Gengsheng Lawrence Zeng and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-07-04 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces the essential concepts of tomography in the field of medical imaging. The medical imaging modalities include x-ray CT (computed tomography), PET (positron emission tomography), SPECT (single photon emission tomography) and MRI. In these modalities, the measurements are not in the image domain and the conversion from the measurements to the images is referred to as the image reconstruction. The work covers various image reconstruction methods, ranging from the classic analytical inversion methods to the optimization-based iterative image reconstruction methods. As machine learning methods have lately exhibited astonishing potentials in various areas including medical imaging the author devotes one chapter to applications of machine learning in image reconstruction. Based on college level in mathematics, physics, and engineering the textbook supports students in understanding the concepts. It is an essential reference for graduate students and engineers with electrical engineering and biomedical background due to its didactical structure and the balanced combination of methodologies and applications,

Download or read book Regularized Image Reconstruction in Parallel MRI with MATLAB written by Joseph Suresh Paul and published by CRC Press. This book was released on 2019-11-05 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regularization becomes an integral part of the reconstruction process in accelerated parallel magnetic resonance imaging (pMRI) due to the need for utilizing the most discriminative information in the form of parsimonious models to generate high quality images with reduced noise and artifacts. Apart from providing a detailed overview and implementation details of various pMRI reconstruction methods, Regularized image reconstruction in parallel MRI with MATLAB examples interprets regularized image reconstruction in pMRI as a means to effectively control the balance between two specific types of error signals to either improve the accuracy in estimation of missing samples, or speed up the estimation process. The first type corresponds to the modeling error between acquired and their estimated values. The second type arises due to the perturbation of k-space values in autocalibration methods or sparse approximation in the compressed sensing based reconstruction model. Features: Provides details for optimizing regularization parameters in each type of reconstruction. Presents comparison of regularization approaches for each type of pMRI reconstruction. Includes discussion of case studies using clinically acquired data. MATLAB codes are provided for each reconstruction type. Contains method-wise description of adapting regularization to optimize speed and accuracy. This book serves as a reference material for researchers and students involved in development of pMRI reconstruction methods. Industry practitioners concerned with how to apply regularization in pMRI reconstruction will find this book most useful.

Download or read book Multi modal Image Reconstruction by Bayesian Methods written by Xiaolong Ouyang and published by . This book was released on 1993 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book The Radon Transform and Some of Its Applications written by Stanley R. Deans and published by Courier Corporation. This book was released on 2007-10-01 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Of value to mathematicians, physicists, and engineers, this excellent introduction to Radon transform covers both theory and applications, with a rich array of examples and literature that forms a valuable reference. This 1993 edition is a revised and updated version by the author of his pioneering work.